投稿時間:2022-06-17 05:27:16 RSSフィード2022-06-17 05:00 分まとめ(27件)

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AWS	AWS Marketplace	Enhance digital security by automating certificate management with CLMaaS in AWS Marketplace	https://aws.amazon.com/blogs/awsmarketplace/enhance-security-automating-certificate-management-clmaas-aws-marketplace/	Enhance digital security by automating certificate management with CLMaaS in AWS MarketplaceCryptography and digital certificates are the security backbone of modern digital enterprises An automated certificate lifecycle management CLM solution helps you efficiently manage your certificates and in turn bolster your security posture Digital transformation cloud migration remote work and Internet of Things IoT create growth opportunities for organizations However they also bring security challenges of …	2022-06-16 19:45:19
AWS	AWS Security Blog	AWS HITRUST CSF certification is available for customer inheritance	https://aws.amazon.com/blogs/security/aws-hitrust-csf-certification-is-available-for-customer-inheritance/	AWS HITRUST CSF certification is available for customer inheritanceAs an Amazon Web Services AWS customer you don t have to assess the controls that you inherit from the AWS HITRUST Validated Assessment Questionnaire because AWS already has completed HITRUST assessment using version in You can deploy your environments onto AWS and inherit our HITRUST CSF certification provided that you use only in scope …	2022-06-16 19:36:31
AWS	AWS Security Blog	AWS HITRUST CSF certification is available for customer inheritance	https://aws.amazon.com/blogs/security/aws-hitrust-csf-certification-is-available-for-customer-inheritance/	AWS HITRUST CSF certification is available for customer inheritanceAs an Amazon Web Services AWS customer you don t have to assess the controls that you inherit from the AWS HITRUST Validated Assessment Questionnaire because AWS already has completed HITRUST assessment using version in You can deploy your environments onto AWS and inherit our HITRUST CSF certification provided that you use only in scope …	2022-06-16 19:36:31
AWS	AWSタグが付けられた新着投稿 - Qiita	【AWS EC2】【RHEL8.6】Zabbix6.0構築（MySQL/Apache）	https://qiita.com/YasumiJP/items/3333050bde793f71f0fe	apache	2022-06-17 04:45:34
Azure	Azureタグが付けられた新着投稿 - Qiita	Azure originからCDNへの転送にかかる料金について	https://qiita.com/fukasawah/items/b16977d718f964a74830	azure	2022-06-17 04:12:19
海外TECH	Ars Technica	Europe’s major new rocket, the Ariane 6, is delayed again	https://arstechnica.com/?p=1861281	development	2022-06-16 19:04:27
海外TECH	MakeUseOf	How to Add a Smile to a Portrait in Photoshop: 4 Ways	https://www.makeuseof.com/photoshop-how-to-add-smile-to-portrait/	photoshop	2022-06-16 19:30:14
海外TECH	MakeUseOf	How to Customize the Scrollbars on Windows 10 and 11	https://www.makeuseof.com/windows-10-11-customize-scrollbars/	default	2022-06-16 19:16:14
海外TECH	DEV Community	Spring Boot Performance Workshop with Vlad Mihalcea	https://dev.to/codenameone/spring-boot-performance-workshop-with-vlad-mihalcea-4jj5	Spring Boot Performance Workshop with Vlad MihalceaA couple of weeks ago we had a great time hosting the workshop you can see below with Vlad Mihalcea It was loads of fun and I hope to do this again soon In this workshop we focused on Spring Boot performance but most importantly on Hibernate performance which is a common issue in production environments It s especially hard to track since issues related to data are often hard to perceive when debugging locally When we have “real world data at scale they suddenly balloon and become major issues I ll start this post by recapping many of the highlights in the talk and conclude by answering some questions we missed We plan to do a second part of this talk because there were so many things we never got around to covering The Problem with show sqlAfter the brief introduction we dove right into the problem with show sql It s pretty common for developers to enable the spring jpa show sql setting in the configuration file By setting this to true we will see all SQL statements performed by Hibernate printed on the console This is very helpful for debugging performance issues as we can see exactly what s going on in the database But it doesn t log the SQL query It prints it on the console Why do we Use Loggers This triggered the question to the audience why does it matter if we use a logger and not System out Common answers in the chat included System out is slow it has a performance overhead But so does loggingSystem out blocking so are most logging implementations but yes you could use an asynchronous loggerNo persistence you can redirect the output of a process to a fileThe reason is the fine grained control and metadata that loggers provide Loggers let us filter logs based on log level packages etc They let us attach metadata to a request using tools like MDC which are absolutely amazing You can also pipe logs to multiple destinations output them in ingestible formats such as JSON so they can include proper meta data when you view all the logs from all the servers e g on Elastic Show sql is Just System OutputIt includes no context It s possible it won t get into your Elastic output and even if it does You will have no context It will be impossible to tell if a query was triggered because of request X or Y Another problem here is the question marks in the SQL There s a very limited context to work with We want to see the variable values not questions Adding a Log with LightrunLightrun lets you add a new log to a production application without changing the source code We can just open the Hibernate file “Loader java and add a new log to executeQueryStatement We can fill out the log statements in the dialog that prompts us Notice we can use curly braces to write Java expressions e g variable names method calls etc These expressions execute in a sandbox which guarantees that they will not affect the application state The sandbox guarantees read only state Once we click OK we can see the log appear in the IDE Notice that no code changed but this will act as if you wrote a logger statement in that line So logs will be integrated with other logs Notice that we print both the statement and the arguments so the log output will include everything we need You might be concerned that this weighs too heavily on the CPU and you would be right Lightrun detects overuse of the CPU and suspends expensive operations temporarily to keep execution time in check This prevents you from accidentally performing an overly expensive operation You can see the log was printed with the full content on top but then suspended to prevent CPU overhead This means you won t have a performance problem when investigating performance issues…You still get to see the query and values sent to the database server Log PipingOne of the biggest benefits of Lightrun s logging capability is its ability to integrate with other log statements written in the code When you look at the log file the Lightrun added statements will appear “in order with the log statements written in code As if you wrote the statement recompiled and uploaded a new version But this isn t what you want in all cases If there are many people working on the source code and you want to investigate an issue logging might be an issue You might not want to pollute the main log file with your “debug prints This is the case for which we have Log Piping Log piping lets us determine where we want the log to go We can choose to pipe logs to the plugin and in such a case the log won t appear with the other application logs This way a developer can track an issue without polluting the sanctity of the log Spring Boot Connection AcquisitionIdeally we should establish the relational database connection at the very last moment You should release it as soon as possible to increase database throughput In JDBC the transaction is on auto commit by default and this doesn t work well with the JPA transactions in Spring Boot Unfortunately we re at a Chicken and Egg problem Spring Boot needs to disable auto commit In order to do that it needs a database connection So it needs to connect to the database just to turn off this flag that should have been off to begin with This can seriously affect performance and throughput as some requests might be blocked waiting for a database connection from the pool If this log is printed we have a problem in our auto commit configuration Once we know that the rest is pretty easy We need to add these two fields that both disable auto commit and tell Hibernate that we disabled it Once those are set performance should be improved Query Plan CacheCompiling JPQL to native SQL code takes time Hibernate caches the results to save CPU time A cache miss in this case has an enormous impact on performance as evidenced by the chart below This can seriously affect the query execution time and the response time of the whole service Hibernate has a statistics class which collects all of this information We can use it to detect problematic areas and in this case add a snapshot into the class SnapshotsA Snapshot AKA Non breaking breakpoint or Capture is a breakpoint that doesn t stop the program execution It includes the stack trace variable values in every stack frame etc It then presents these details to us in a UI very similar to the IDE breakpoint UI We can traverse the source code by clicking the stack frames and see the variable values We can add watch entries and most importantly we can create conditional snapshots this also applies to logs and metrics Conditional snapshots let us trigger the snapshot only if a particular condition is met A common problem is when a bug in a system is experienced by a specific user only We can use a conditional snapshot to get stack information only for that specific user Eager FetchWhen we look at logs for SQL queries we can often see that the database fetches a lot more than what we initially asked for That s because of the default setting of JPA relations which is EAGER This is a problem in the specification itself We can achieve significant performance improvement by explicitly defining the fetch type to LAZY We can detect these problems by placing a snapshot in the loadFromDatasource method of DefaultLoadEventListener In this case we use a conditional snapshot with the condition event isAssociationFetch As a result the snapshot will only trigger when we have an eager association which is usually a bug It means we forgot to include the LAZY argument to the annotation As you can see this got triggered with a full stack trace and the information about the entity that has such a relation You can use this approach to detect incorrect lazy fetches as well Multiple lazy fetches can be worse than a single eager fetch so we need to be vigilant Open Session in View Anti PatternOn the surface it doesn t seem like we re doing anything wrong We re just fetching data from the database and returning it to the client But the transaction context finished when the post controller returned and as a result we re fetching from the database all over again We need to do an additional query as data might be stale Isolation level might be broken and many bugs other than performance might arise This creates an N problem of unnecessary queries We can detect this problem by placing a snapshot on the onInitializeCollection call and seeing the open session Now that we see the problem is happening we can solve the problem by defining spring jpa open in view falseIt will block you from using this approach Q amp AThere were many brilliant questions as part of the session Here are the answers Could you please describe a little bit about Lightrun Lightrun is a developer observability platform As such it lets you debug production safely and securely while keeping a tight lid on CPU usage It includes the following pieces Client IDE Plugin Command LineManagement ServerAgent running on your server to enable the capabilitiesI wrote about it in depth here Could Lightrun Work Offline Since you re debugging production we assume your server isn t offline However Lightrun can be deployed on premise which removes the need for an open to the Internet environment Wondering about this sample will this be available for our reference The code is all here As the Instrumentation manipulation happens via a Server given that I do not host the instrumentation server myself what kind and what amount of data is being transmitted Is the data secured or encrypted in any way The instrumentation happens on your server using the agent The Lightrun server has no access to your source code or bytecode Source code or bytecode never goes on the wire at any stage and Lightrun is never exposed to it All transmissions are secured and encrypted Certificates are pinned to avoid a man in the middle attack The Lightrun architecture received multiple rounds of deep security reviews and is running in multiple Fortune companies Finally all operations in Lightrun are logged in an administrator log which means you can track every operation that was performed and have a full post mortem trail You can read more about Lightrun security here As mentioned these logs are aged out in hr Is it possible to save those and re use them for later use rather than creating log entries manually every time Lightrun actions default to expire after hour to remove any potential unintentional overhead You can set this number much higher which is useful for hard to reproduce bugs Notice that when an action is expired you can just click it and re create it It will appear in red within the IDE and can still be used for reference Is IntelliJ IDEA the only way to add breakpoints logging Or how is debugging with Lightrun done in production You can use IntelliJ also PyCharm and WebStorm as well as VSCode VSCode dev and the command line These connect to production through the Lightrun server The goal is to make you feel as if you re debugging a local app while extracting production data Without the implied risks Is there any case where eager loading should be configured always for One to Many or Many to Many or Many to One relations I always configure lazy loading for the above relations Is it okay Yes If you see that you keep fetching the other entity then eager loading for this case makes sense Having eagerness as the default makes little sense for most cases Do we need to restart an application with the javaagent The agent would run in the background constantly It s secure and doesn t have overhead when it isn t used If we are using other instrumentation tools like say AppDynamics or dynatrace ……does this work alongside This varies based on the tool Most APMs work fine besides Lightrun because they hook up to different capabilities of the JVM Does this work with GraalVM Not at this time since GraalVM doesn t support the javaagent argument We re looking for alternative approaches but hopefully the GraalVM team will have some solutions Is it free to use Yes Check out lightrun com freeDoes it impact app performance Yes but it s minimal Under when no actions are used and under with multiple actions Notice you can tune the amount of overhead in the agent configuration Does it work for Scala and Kotlin Yes How to use it in production without IDE The IDE will work even for production since you don t connect directly to the production servers and don t have access to them The IDE connects to the Lightrun management server only This lets your production servers remain segregated Having said that you can still use the command line interface to get all the features discussed here and much more Apart from injecting loggers what other stuff can we do The snapshot lets you get full stack traces with the values of all the variables in the stack and object instance state You can also include custom watch expressions as part of the snapshot Metrics let you add counters how many times did we reach this line tictocs how much time did it take to perform this block method duration similar to tictocs but for the whole method and custom metrics You can also add conditions to each one of those to narrowly segment the data How do we hide sensitive properties from beans Say Credit card number of user Lightrun supports PII Reduction which lets you define a mask e g credit card that would be removed before going into the logs This lets you block an inadvertent injection into the logs It also supports blocklists which let you block a file class group from actions This means a developer won t be able to place a log or snapshot there How can we use it for performance testing I made a tutorial on this here When working air gapped on prem is required how do you provide the Server as a jar or docker… This is something our team helps you set up Will it consume much more memory if we run with the Lightrun agent This is minimal Running the petclinic demo on my Mac with no agent produces this in the system monitor With the agent we have this At these scales a difference of mb is practically within the margin of error It s unclear what overhead the agent has if at all FinallyThis has been so much fun and we can t wait to do it again Please follow Vlad Tom and myself for updates on all of this There are so many things we didn t have time to cover that go well beyond slow queries and spring data nuances We had a really cool demo of piping metrics to Grafana that we d love to show you next time around	2022-06-16 19:05:06
海外TECH	DEV Community	Optical Character Recognition Technology for Business Owners	https://dev.to/evgeniykrasnokutsky/optical-character-recognition-technology-for-business-owners-587n	Optical Character Recognition Technology for Business OwnersWith the growing interest in OCR and Machine Learning more and more business owners are looking for ways to apply this killing combination to optimize their business processes and if you are one of them this article is for you Let s find out more about what OCR is how OCR powered with machine learning is different from the original technology and how it can be used in business What is OCR and How Does It Work Optical character recognition OCR also known as text recognition technology converts any kind of image containing written text into machine readable text data OCR allows you to quickly and automatically digitize a document without the need for manual data entry That s why OCR is commonly used for business flow optimization and automation The output of OCR is further used for electronic document editing and compact data storage and also forms the basis for cognitive computing machine translation and text to speech technologies There are different types of OCR depending on the tasks they solve Intelligent Word Recognition IWR is used for the recognition of unconstrained handwritten words instead of recognition of individual characters Intelligent Character Recognition ICR is a more advanced form of OCR based on updating algorithms to gather more data about variations in hand printed characters Optical Word Recognition OWR scans typewritten text word by word Optical Mark Recognition OMR is used to identify the information that people mark on surveys tests etc Let s find out how OCR works The functioning of the traditional optical character recognition system consists of three stages image pre processing character recognition post processing STEP CHECKING THE DOCUMENT TYPE amp IMAGE PRE PROCESSINGThe main challenge of text recognition is that each document template has its own set of entities values and location of entities in the document For OCR software to work accurately it must be able to identify different types of documents and run the correct predefined pipeline based on that For example PDF documents may or may not contain a text layer If the PDF does not contain a text layer we must process it differently than if it did After choosing the right pipeline the image comes to the pre processing step This is a preparation step that affects the outcomes Image pre processing helps to remove image noise and increase the contrast between the background and text which will help improve text recognition At this step the OCR program converts the document to a black and white version and then analyzes it for the presence of light and dark areas Light areas are identified as the background while dark areas are identified as characters to be processed STEP CHARACTER RECOGNITIONWith the use of feature detection and pattern recognition algorithms a single character is detected Then a set of the characters are assembled into words and sentences Characters are identified using pattern recognition or feature detection algorithms Pattern recognition is a method based on finding matches between the image text and text samples embedded in the system in various fonts and formats This method works best with typescript and it doesn t work well when new fonts are encountered that are not included in the system The feature detection algorithm makes it possible to recognize new characters by applying rules regarding character s individual features Such features may include the number of slanted lines intersecting lines or curves in the comparison symbol Most often OCR programs with feature detection use classifiers based on machine learning or neural networks to process characters Classifiers are used to compare image features with stored examples in the system and select the closest match The feature detection algorithm is good for unusual fonts or low quality images where the font is distorted STEP POST PROCESSINGOnce a symbol is identified it is converted into a code that can be used by computer systems for further processing We should mention that the output of any OCR and OCR related technology algorithm has a lot of noise and false positives It makes it difficult to use OCR s output directly so we have to Filter out noisy outputs and false positivesCombine recognized entities with their extracted meaningCheck for possible mistakes and prevent output to the user if anyBased on statistical data the system can detect some typical OCR errors for example those related to the similarity of characters and words Thus at this stage the system corrects flaws in order to improve the quality of the OCR output OCR is a Machine Learning and Computer Vision TaskOptical character recognition is one of the main computer vision tasks Сomputer vision allows systems to see and interpret real world objects and recognize texts separating them from complex backgrounds Early versions of OCR had to be trained with images of each character and could only work with one font at a time Modern machine learning algorithms make the text recognition process more advanced and provide a higher level of recognition accuracy for most fonts regardless of input data formats Advances in machine learning ML have given a new impetus to the development of OCR significantly increasing the number of its applications With enough training data the OCR machine learning algorithm now can be applied to any real world scenario that requires identification and text transformation For example receipts scanning scanning of printed text with the further conversion of it into synthetic speech traffic sign recognition license plate recognition etc The use of modern machine learning algorithms can significantly improve the technology and expand its use cases to more complicated ones For example OCR with deep learning allows not only image classification but image analysis and extraction of more complex data from different objects including hundreds of handwritten fonts or languages OCR Business CasesOCR application in business has numerous scenarios Since text recognition using machine learning provides greater accuracy than the earlier versions of optical character recognition this allows business owners to create OCR solutions to address a wider range of business challenges Modern OCR systems are used in security banking insurance medicine communications retail companies and other industries Use cases for OCR technology include checking test answers real time translations recognizing street signs Google Street View searching through photos Dropbox and more Optical character recognition is also widely used by security teams This technology helps to analyze and process documents such as a driver s license or ID for verifying a person s identity For each case a completely different OCR solution is used OCR IN FINANCIAL SERVICESFinancial transactions involve a huge amount of data entry Manual processing of this data takes a lot of time and effort while digitization of financial documents and extracting the necessary information from them using OCR makes business processes smooth and optimized As a result the OCR technology improves customer onboarding and enhances the overall customer experience Optical character recognition uses in the banking and financial sector include the following Client onboarding Whatever financial transactions you want to perform whether it be opening an account withdrawing cash or transferring money you first need to authenticate to prove your identity OCR technology provides a fully automated onboarding process consisting of scanning an identity document e g ID passport or driver s license extracting the necessary data using OCR e g name dates of birth gender photo signature etc and checking it For example the OCR engine can inspect in real time whether the provided signature matches the signature on the identity document Scan to pay feature Manual entry of payment details does not exclude errors and takes more time than expected The scan to pay feature uses optical character recognition to instantly capture invoice data and automatically process it The user only needs a smartphone camera to do this for example you may need to take a photo of your credit card OCR can also act as an extra security feature when making payments Usually users store cardholder data in the application desiring not to enter the card number and other details every time With OCR all you need is to enable the OCR feature which extracts data in seconds for each new payment and then removes it Receipt recognition OCR allows automating data extraction from receipts for further accounting archiving or document analytics You can find this feature implemented in financial assistant apps with money tracking elements for automated data entry of expenses and expense categories Expensify is an example of such an application The high variability and often low quality of receipts are the main challenges for accurate receipt recognition with OCR In such a case the rule based approach cannot be effective and this is where optical character recognition with deep learning comes in The deep learning approach to OCR allows the system to learn from the received data and improve This technology lets training a model to identify regions of interest RoI in an image that are highly likely to contain text ignoring redundant data such as the background Loan processing OCR and machine learning text recognition tools can speed up the processing of loan and mortgage applications by up to percent Automation of data entry makes the process of reviewing applications and approving or rejecting them much faster and more cost effective for the company AI algorithms can parse the required data from the application to determine if it should be approved or rejected based on the financial institution s rules Use cases of OCR in finance are not limited to the above The technology can be used for processing other financial documents like invoices contracts bills financial reports etc OCR IN HEALTHCAREOСR cases in the healthcare industry are closely related to data management According to the World Economic Forum hospitals produce an average of petabytes of data per year This data includes medical reports prescription forms claims laboratory test results and medical records The digitalization of medical documents and the efficient extraction of data from them is a critical aspect of the functioning of a healthcare institution By applying optical character recognition technology hospitals can translate papers into a digital format much faster and store them as PDF documents that can be easily searched using keywords Electronic medical records solve one of the main problems of hospitals the loss of medical information about patients Also OCR allows data to be pulled from certificates or test results and sent to hospital information management systems HIMS for integration into patient records thus forming a complete medical history of patients Pharmaceutical systems can take advantage of OCR as well Powered with an OCR module such systems allow you to scan medical prescriptions and import them into software to check the presence of the medicine in pharmacy databases or even use it to control picking robots OCR technology is also used to help people with visual impairments By scanning the text on the image the OCR system provides the base for using text to speech technology All you have to do is scan the text to get synthetic speech output For example the Voice Speech Scanner app uses the smartphone s camera to capture a photo with text and then reads all of the text back This is a new level of assistance to people with visual impairments after the technology of deep learning image captioning which provides automatic generation of textual description of an image OCR IN RETAILRetailers produce many different documents such as packing lists invoices purchase orders receipts product descriptions and others These are huge amounts of information which however are not used properly due to the complex and time consuming processing Using OCR with machine learning retailers can experience the rapid development of internal business processes and improve the customer experience by making the most of the existing data For example merchants can extract valuable insights from purchase order analytics to create more effective marketing campaigns promotions and manage pricing better By converting invoices and receipts into digital format and incorporating them into accounting systems retail companies get a chance to automate their accounting processes Implementing OCR is a great way to handle the large workloads of retail workers With automatic data entry and data extraction employees are left with only manual verification to achieve optimal results Cases of using OCR in retail are not limited to the above The text recognition feature can address some specific challenges of retail companies For example the technology can be helpful for wine merchants who offer a wide range of products With OCR based wine label recognition users can take a photo of a wine label and get product information such as reviews description etc to help them make the right choice OCR IN SECURITY AND LAW ENFORCEMENTAlmost any industry can take advantage of OCR as part of its security strategy Using OCR powered by machine learning companies have a chance to build advanced user authentication and verification systems Usually manual comparison documents with provided personal info and a selfie are used to verify the authenticity of the identifier presented by the user The OCR model eliminates these manual efforts by scanning ID cards passports or driver s licenses and checking their authenticity comparing them with the info in the database In this case the OCR engine must first recognize the document type For example if a user chooses to authenticate with a driver s license the document they upload to the system must conform to that document format Then the system should analyze and process uploaded user documents to get relevant data Since documents of the same type may have a different format depending on the country or state the system must be able to find and extract the necessary data from all variations Using deep learning algorithms helps the OCR system understand the relative positional relationship among different text blocks and combine pairs of semantically connected blocks of text to find relevant data such as name date of birth etc It is also worth mentioning that secure authentication OCR software should have features to prevent spoofing attempts when parsing documents Anti spoofing techniques will help the system detect fake ID scans and other fraudulent attempts Optical character recognition technology is also widely used for automatic number plate recognition ANPR This technology is very helpful for cameras that enforce traffic laws ANPR is also used for electronic toll collection on toll roads car park management bus lane enforcement and traffic management In general systems based on OCR assistance ensure road safety in most countries of the world For example in the USA all police departments use some form of ANPR According to the California State Auditor s report the Los Angeles Police Department LAPD alone has amassed over million license plate scans In the UK automatic number plate recognition is used to record the movement of vehicles from nearly cameras that capture millions of records daily This data helps deter and stop crime including organized crime groups and terrorists Hardware for OCRA high quality text recognition system is a well coordinated work of software and hardware The hardware required for OCR is a special scanner or just a camera on your phone The hardware is used for taking an image of a text on a paper sheet and the software does the rest of the work by recognizing extracting a text out of an image Hardware plays the role of the eyes receptors of software And software plays the role of the brain that processes the eye s information and extracts meaning from the perceived data Modern OCR solutions can turn a smartphone or PC camera into a full fledged document scanner Most current OCR applications upload images to a server for recognition and then return the recognition output to the client Many iOS and Android app creators develop their own intelligent camera interfaces that detect document borders correct perspective and optimize image quality The output of mobile OCR depends primarily on the mobile device s camera and shooting conditions Out of the box Solutions vs Custom OCR DevelopmentWhen a business owner needs software for optical character recognition the question arises of which solution is better to use ready made or customized solution There are many options for OCR systems on the market but it is important to understand that they are mostly focused on processing standard business processes and may not meet your specific needs That s why it s so important to determine the goals and requirements of your project and then explore the options COMMERCIAL VS OPEN SOURCE OCR SOLUTIONSThere are commercial and open source OCR solutions Commercial ones are usually provided as a service GoogleOCR is an example of such software If you need to quickly implement OCR functionality in your application then GoogleOCR is a great choice But it is worth remembering that this solution is paid and requires an Internet connection Open source OCR can be integrated as separate client application cloud services Such solutions don t require a direct payment for the service but involve the cost of maintaining the infrastructure for the functioning of OCR for example a microservice Having a microservice also requires an Internet connection for OCR to work However there are also standalone optical character recognition systems that can function without the Internet In this case the user device must provide enough computing resources to solve the OCR task Also open source OCR may have slightly lower output quality compared to commercial solutions in some specific tasks Customization options are another key factor in choosing OCR Commercial solutions most often cannot be customized to the specific needs of the client even if the datasets necessary for this are available Open source OCR can be tailored to specific user requirements for example such as handwriting recognition in a rare language Limitations of OCR Technology and How to Overcome ThemAlthough optical character recognition is a widely used technology it has limitations especially if we talk about classical text recognition systems Combining OCR with computer vision and deep learning improves the accuracy of OCR in many cases but it is important to understand that it is impossible to achieve results and you will need additional software solutions to improve the outcomes The list of key limitations of optical character recognition technology includes the following The lower the quality of an image the lower the quality of the OCR outputThe OCR result is very dependent on the quality of the original image which is why the image pre processing stage is so important Common OCR errors include misreading letters missing unreadable letters or mixing text from adjacent columns The most commonly used methods for normalizing an image include aligning and rotating the document removing blur and applying filters and deleting elements that are not characters like tables separator lines etc Complex image backgroundElements such as small dots or sharp edges that make up the background can often be read as characters and distort the results of the text recognition process That s why the pre processing stage for OCR should include noise removal and text field isolation To overcome the issue of the noise presence like dots lines stains etc in the background nowadays OCR approaches use computer vision based algorithms trained on augmented data sets Augmented data sets are just regular data sets with artificially added noises to teach an OCR model to tackle the noise properly OCR works better with printed text than with handwritten textHandwritten fonts have hundreds of variations which complicates the text recognition process Plus many options include cases of connecting letters which are difficult for the system to separate and which lead to a distorted output For handwriting recognition the development team needs to train the OCR model using deep learning algorithms and advanced computer vision engines It s worth noting that the more quality the dataset that is used to train the model the faster it will improve and bring better results In this case it s better to use less data but the most relevant Using huge datasets which do not accurately represent your particular project s real data will not yield successful results Other limitations of optical character recognition technology includeSmall text font size of less than points Form processing because it requires systems where OCR is only a small part of the mechanism Blurry copies Sometimes inaccuracies can be restored from context but when it comes to names or numbers the context may not be enough to restore them Document formatting may be lost during text scanning For example bold italic amp underline texts are not always recognized and require subsequent formatting of the document which is a separate task The result of OCR always requires spell checking and reformatting for the desired layout Key TakeawaysOptical Character Recognition OCR based on AI and machine learning is a widely used technology for text recognition and digitalization of documents Even though OCR is not yet accurate its use cases are growing with the development of deep learning and computer vision Today one or another type of OCR is used in retail communications finance healthcare security tourism and other industries The definition of business goals greatly influences the approaches architecture and tools that will be used to develop OCR software The data should correspond to the objectives of your project and be as real as possible	2022-06-16 19:03:23
Apple	AppleInsider - Frontpage News	Apple's iOS 16 lets you remove 30 stock apps	https://appleinsider.com/articles/22/06/16/apples-ios-16-lets-you-remove-29-stock-apps?utm_medium=rss	Apple x s iOS lets you remove stock appsApple is increasing the number of pre installed iPhone apps that can be removed with the beta of iOS now allowing to be deleted As Apple releases the first beta of iOS developers have been finding what unannounced new features are being added ーand now removed After some years of increasing how many of its own apps can now be removed Apple s iOS brings the total to The iOS apps that can be removed may change over the course of the beta though it s likely the total will either increase or stay the same Read more	2022-06-16 19:30:40
海外TECH	Engadget	'Overwatch 2' won't have loot boxes	https://www.engadget.com/overwatch-2-no-loot-boxes-194001374.html?src=rss	x Overwatch x won x t have loot boxesOverwatch will get rid of one of the first game s most infamous elements Blizzard has confirmed at a reveal event that that the new team based shooter won t have loot boxes when it premieres October th Instead you ll get the items you want through either a Battle Pass or a quot consistently updated quot in game store You won t have to roll the dice wondering if you ll get a special character skin or emote Blizzard also used the event to show what you can expect for the first two seasons The developer will provide free updates every nine weeks to keep things fresh with progression applying across game platforms The first season will include three new heroes Sojourn Junker Queen and an unidentified third six more maps plus extra skins and a new game mode The second season kicking off December th will add a new take hero another map and still more cosmetics In you can expect a new quot PvE experience quot that advances the story The approach to loot boxes is a relative about face The company has kept the random boxes in Overwatch ever since launch and has been defensive Blizzard even refused to release Diablo Immortal in Belgium and the Netherlands due to those countries laws banning loot box mechanics as a form of gambling With Overwatch the team is acknowledging the backlash There might not have been much choice Overwatch has maintained a largely steady player count and even grown slightly over the years with ActivePlayer io data indicating an average of million players per month as of May However it s no secret that some players hate loot boxes and might be wary of playing the new game if they persist As it stands US agencies like the Federal Trade Commission have investigated loot box systems in the past Whatever the motivations for scrapping the boxes the decision could help Blizzard avoid legal trouble in its home country	2022-06-16 19:40:01
海外科学	NYT > Science	Monkeypox Outbreak Poses ‘Real Risk’ to Public Health, W.H.O. Official Says	https://www.nytimes.com/2022/06/15/world/europe/monkeypox-outbreak-europe.html	Monkeypox Outbreak Poses Real Risk to Public Health W H O Official SaysDr Hans Kluge the organization s director for Europe said that the longer the virus circulated the wider its reach would be	2022-06-16 19:02:45
ニュース	BBC News - Home	Archbishop of Canterbury apologises over Church fund's link to slavery	https://www.bbc.co.uk/news/uk-61834511?at_medium=RSS&at_campaign=KARANGA	slave	2022-06-16 19:55:24
ニュース	BBC News - Home	Kim Kardashian: Marilyn Monroe's gown not damaged, Ripley's claims	https://www.bbc.co.uk/news/entertainment-arts-61801906?at_medium=RSS&at_campaign=KARANGA	museum	2022-06-16 19:01:29
ビジネス	ダイヤモンド・オンライン - 新着記事	仕事が早い人と遅い人を分ける「4つの差」、単純スキルでも極めると効果絶大 - 「40代で戦力外」にならない！新・仕事の鉄則	https://diamond.jp/articles/-/304551	仕事が早い人と遅い人を分ける「つの差」、単純スキルでも極めると効果絶大「代で戦力外」にならない新・仕事の鉄則限られた時間の中で多くの仕事をこなすビジネスパーソンにとって、「仕事のスピードを上げる」ことは成果を出す上で重要な要素だ。	2022-06-17 04:55:00
ビジネス	ダイヤモンド・オンライン - 新着記事	北國フィナンシャルの株価急騰、「ファンドの影響力」が銀行株で高まる裏事情 - 橋本卓典の銀行革命	https://diamond.jp/articles/-/304910	株式市場	2022-06-17 04:50:00
ビジネス	ダイヤモンド・オンライン - 新着記事	トルコ経済が7四半期連続プラス成長、景気回復はロシア富裕層のおかげ？ - 西濵徹の新興国スコープ	https://diamond.jp/articles/-/304916	景気回復	2022-06-17 04:45:00
ビジネス	ダイヤモンド・オンライン - 新着記事	離婚調停「弁護士なし」だと危うい5つのケース、裁判所は“味方”ではない - 弁護士ドットコム発	https://diamond.jp/articles/-/304807	離婚調停「弁護士なし」だと危ういつのケース、裁判所は“味方ではない弁護士ドットコム発離婚調停は弁護士をつけずに本人で申し立てる人も多いが、調停が成立したり、離婚の合意書を作成したりした後では、基本的に覆すことはできない。	2022-06-17 04:40:00
ビジネス	ダイヤモンド・オンライン - 新着記事	もし「経営の神様・松下幸之助」が現代の社長だったら…先見性溢れる3つの教え - 今週もナナメに考えた　鈴木貴博	https://diamond.jp/articles/-/304915	松下幸之助	2022-06-17 04:35:00
ビジネス	ダイヤモンド・オンライン - 新着記事	フェイクニュース製造村の戦慄…月収5万円の村民が偽記事でベンツを買うまで - ＤＯＬ特別レポート	https://diamond.jp/articles/-/304894		2022-06-17 04:32:00
ビジネス	ダイヤモンド・オンライン - 新着記事	運送業の倒産・買収が「2024年問題」で増加の兆し、東京商工リサーチが解説 - 倒産のニューノーマル	https://diamond.jp/articles/-/304885	運送業の倒産・買収が「年問題」で増加の兆し、東京商工リサーチが解説倒産のニューノーマル企業倒産は政府のコロナ関連支援策で小康状態が続くが、道路貨物運送業の倒産が止まらない。	2022-06-17 04:30:00
ビジネス	ダイヤモンド・オンライン - 新着記事	怪しくない仕事用マッチングアプリ「Yenta」、営業のやり手も使う魅力とは - 仕事を256倍速くするツールを探せ！	https://diamond.jp/articles/-/304882	yenta	2022-06-17 04:20:00
ビジネス	ダイヤモンド・オンライン - 新着記事	企業が苦悩する「デジタル人材の定着と育成」、金融老舗・クレディセゾンに入社したCTOの挑戦 - 進化する組織	https://diamond.jp/articles/-/304932		2022-06-17 04:15:00
ビジネス	ダイヤモンド・オンライン - 新着記事	「覚える」のは非効率！「メモする」ほうが仕事の精度は断然上がる - 仕事のミスが絶対なくなる頭の使い方	https://diamond.jp/articles/-/304578	「覚える」のは非効率「メモする」ほうが仕事の精度は断然上がる仕事のミスが絶対なくなる頭の使い方“脳のメモ帳ワーキングメモリは、鍛えても容量が増えない。	2022-06-17 04:10:00
ビジネス	ダイヤモンド・オンライン - 新着記事	20代独身男性「4割がデート経験なし」だけ切り取られた調査の大事な内容 - News&Analysis	https://diamond.jp/articles/-/304538	newsampampanalysis	2022-06-17 04:05:00
ビジネス	東洋経済オンライン	新幹線延伸で大盛況の予感､福井ご当地鉄道事情 敦賀駅は関西と北陸をつなぐ｢鉄道の要衝｣ | トラベル最前線 | 東洋経済オンライン	https://toyokeizai.net/articles/-/596370?utm_source=rss&utm_medium=http&utm_campaign=link_back	九州新幹線	2022-06-17 04:30:00