Want to do handwritten OCR? This blog is a comprehensive overview of the latest methods of handwritten text recognition using deep learning. We've reviewed the latest research and papers and have also built a handwriting reader from scratch. Nanonets OCR API has many interesting use cases. Talk to a Nanonets AI expert to learn more about handwritten text recognition. Introduction Optical Character
handwriting-recognition/explainer.md at main · WICG/handwriting-recognition
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How Disney Improved Activity Recognition Through Multimodal Approaches with PyTorch
by Monica Alfaro, Albert Aparicio, Francesc Guitart, Marc Junyent, Pablo Pernias, Marcel Porta, and Miquel Àngel Farré (former Senior Technology Manager) Introduction Among the many things Disney Media & Entertainment Distribution (DMED) is responsible for, is the management and distribution of a huge array of media assets including news, sports, entertainment and features, episodic programs, mark
論文紹介 / An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
第六回 全日本コンピュータビジョン勉強会 Transformer論文読み会 にて、 "An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale" [Dosovitskiy et al., ICLR 2021] …
はじめに 前回は店舗における画像認識の活用事例を見てきましたが、今回は駅や空港、駐車場などの交通機関および地域まるごと顔認証決済という取り組みなどを紹介します。現代の知識習得は動画活用がポイントですので、ベンダー各社が制作した動画も紹介しています。ぜひ、どこまで実現できているかを映像で確かめてみてください。 交通機関における画像認識 1. 電車 私のような切符世代にとっては駅の自動改札でさえ夢のような産物なのですが、さらに進化した「顔パス改札」が始まっています。進んでいるのはやはり中国で、2019年頃から深セン、成都、太原、鄭州、広州、南寧、昆明、西安、ハルピン、貴陽、福州など各都市の地下鉄で顔認証改札が続々導入されています。スマホで顔を登録して顔パス認証する様子を四川省の成都地下鉄の動画でご覧ください。 私のようにモバイルSuicaのタッチで満足している人も多いでしょうが、中国がやるなら
GitHub - JDAI-CV/FaceX-Zoo: A PyTorch Toolbox for Face Recognition
FaceX-Zoo is a PyTorch toolbox for face recognition. It provides a training module with various supervisory heads and backbones towards state-of-the-art face recognition, as well as a standardized evaluation module which enables to evaluate the models in most of the popular benchmarks just by editing a simple configuration. Also, a simple yet fully functional face SDK is provided for the validatio
All it takes to fool facial recognition at airports and border crossings is a printed mask, researchers found
Researchers with an artificial-intelligence firm said they were able to fool facial-recognition software at an airport and mobile-payment kiosks using a printed mask, highlighting security vulnerabilities.The researchers said the tests, which were carried out across three continents, fooled two mobile-payment systems, a Chinese border checkpoint, and a passport-control gate at Amsterdam's Schiphol
GitHub - argmaxinc/WhisperKit: On-device Speech Recognition for Apple Silicon
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ChemDataExtractor：シンプルテキストから固有表現抽出（Named Entity Recognition; NER）を行ってみる - Qiita
概要 論文や特許文献から材料名，化合物名，そしてそれに紐づく物性値を自動的に取得したり抽出したりしてマイニングしたい．そのようなときに使われるのが，近年ではpythonライブラリのChemDataExtractorに勢いがあります．あまり日本語の解説サイトがないので，メモとして書き残しておきます． ChemDataExtractor（導入編） 今回のテキスト解析はオープンジャーナルのNanomaterialsから，以下の有機ELの青色発光のTADF論文から例文を使います． Nanomaterials 2019, 9(12), 1735; https://doi.org/10.3390/nano9121735 A Novel Design Strategy for Suppressing Efficiency Roll-Off of Blue Thermally Activated Dela
OpenCVとdlibを使って顔認識(face recognition)してみる【前編】｜Tech Press | テックプレス
いきなりの実装に入る前に、簡単に理論のおさらいと基本的な実装方法をおさえておきます。 その後に、ウェブカメラを使って顔を検出し、似ている人を選択するアプリを作成します。 顔認識で検出するまでの流れ 画像もしくは動画を見て顔を見つける顔に焦点を合わせ、顔が正面を向いていなくても人だと認識できる目の大きさ、顔の長さなど他の人と区別するために固有の特徴量を選択検出した顔の特徴を、他の人と比較して一番似ている人を決定 顔を見つける 顔かどうかを判定するためには、いくつか方法があります。 まず、ピクセルを明るさの差でグラデーションに置き換えることで、明るさの変化の方向だけを考えることができます。 そうすれば、画像の基本パターンを知ることができるので顔の特徴を抽出しやすくなります。 この手法はHOGと呼ばれものです。 顔の向きの不一致 正面を向いている顔は認識しやすいのですが、斜めや横を向いていると途
GitHub - microsoft/Recognizers-Text: Microsoft.Recognizers.Text provides recognition and resolution of numbers, units, date/time, etc. in multiple languages (ZH, EN, FR, ES, PT, DE, IT, TR, HI, NL. Partial support for JA, KO, AR, SV). Packages available a
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Recent work has shown that self-attention can serve as a basic building block for image recognition models. We explore variations of self-attention and assess their effectiveness for image recognition. We consider two forms of self-attention. One is pairwise self-attention, which generalizes standard dot-product attention and is fundamentally a set operator. The other is patchwise self-attention,
High-performance speech recognition with no supervision at all What the research is:Whether it’s giving directions, answering questions, or carrying out requests, speech recognition makes life easier in countless ways. But today the technology is available for only a small fraction of the thousands of languages spoken around the globe. This is because high-quality systems need to be trained with l
Amazon Rekognition で顔認証 / Facial Recognition with Amazon Rekognition
Amazon Rekognition を用いた顔認証によるイベント受付ソリューションについて紹介します。AWS Solutions - Auto Check-In App としてテンプレート公開予定です。
‘Farewell Convolutions’ – ML Community Applauds Anonymous ICLR 2021 Paper That Uses Transformers for Image Recognition at Scale | Synced
‘Farewell Convolutions’ – ML Community Applauds Anonymous ICLR 2021 Paper That Uses Transformers for Image Recognition at Scale ICLR 2021 paper An Image Is Worth 16x16 Words: Transformers for Image Recognition at Scale suggests Transformers can outperform top CNNs on CV at scale. A new research paper, An Image Is Worth 16×16 Words: Transformers for Image Recognition at Scale, has the machine learn
GitHub - yiskw713/pytorch_template: Pytorch Implementation example of Image Classification with flowers recognition dataset
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Involution: Inverting the Inherence of Convolution for Visual RecognitionをEfficientNetで試してみた
Involution: Inverting the Inherence of Convolution for Visual RecognitionをEfficientNetで試してみた 畳み込み演算の解析 まず、畳み込み演算について説明します。 高さHHH、幅WWW、 チャンネル数CiC_iCiの特徴マップをX∈RH×W×Ci\mathbf{X} \in \mathbb{R}^{H×W×C_i}X∈RH×W×Ciとし、各ピクセルでは、Xi,j∈RCi\mathbf{X}_{i,j} \in \mathbb{R}^{C_i}Xi,j∈RCiとします。また、K×KK×KK×Kのカーネルを持つC0C_0C0個の畳み込みフィルターを、Fk∈RCi×K×K,k=1,2,⋯ ,C0\mathcal{F}_k \in \mathbb{R}^{C_i × K × K}, k=1, 2, \cdo
Coronavirus: Russia uses facial recognition to tackle Covid-19 As Russian cities go into lockdown to try to contain coronavirus, Moscow is using the latest technology to keep track of residents. City officials are using a giant network of tens of thousands of cameras - installed with facial recognition software - which they plan to couple with digital passes on people’s mobile phones. It’s prompte
論文まとめ：2D/3D Pose Estimation and Action Recognition using Multitask Deep Learning - Qiita
論文まとめ：2D/3D Pose Estimation and Action Recognition using Multitask Deep LearningMachineLearningDeepLearningCNNPoseEstimation はじめに CVPR2018 から 以下の論文 [1] D. C. Luvizon, et. al "2D/3D Pose Estimation and Action Recognition using Multitask Deep Learning", CVPR2018 のまとめ arXiv: https://arxiv.org/abs/1802.09232 著者らのコード: https://github.com/dluvizon/deephar Keras で実装されてる 現状では日本語でまとめた記事は見当たらない 概要 単眼 RGB 画像か
Facebook to stop using facial recognition, delete data on over 1 billion people
Enlarge / With an image of himself on a screen in the background, Facebook co-founder and CEO Mark Zuckerberg testifies before the House Financial Services Committee in the Rayburn House Office Building on Capitol Hill October 23, 2019, in Washington, DC. Facebook introduced facial recognition in 2010, allowing users to automatically tag people in photos. The feature was intended to ease photo sha
KuroNet: Regularized Residual U-Nets for End-to-End Kuzushiji Character Recognition - SN Computer Science
Kuzushiji, a cursive writing style, had been used in Japan for over a thousand years starting from the eighth century. Over 3 million books on a diverse array of topics, such as literature, science, mathematics and even cooking are preserved. However, following a change to the Japanese writing system in 1900, Kuzushiji has not been included in regular school curricula. Therefore, most Japanese nat
Philosophy We strive to create an environment conducive to many different types of research across many different time scales and levels of risk. Learn more about our Philosophy Learn more
電子投票における生体認証の実装の分析：インターネット投票で顔識別（facial recognition）の利用は可能か？
Cybernetica社のサイバー専門家によって作成された「電子投票における生体認証（biometrics）の実装の分析（技術文書：バージョン1.1）」が公開されました。本文書を読み解くことで、エストニアの電子投票の仕組みの理解が深まる内容になっています。 電子投票における生体認証の実装（2021年7月2日：エストニア語） 技術的な実現可能性、法的な問題、開発作業量の評価などを含む本分析では、電子投票に顔認識（facial recognition）を実装することは可能だが、プライバシー侵害と技術の複雑さの増大により、現在の「メリットを上回る可能性のあるリスク」を追加しています。 電子投票システムの技術面を支援するエストニア情報システム局（RIA)の見解では、「現在、顔認識技術について合意されたセキュリティ基準はなく、一度に多数の人々によって使用されるという広範な公的慣行がない」ので、電子投
[DL輪読会]SlowFast Networks for Video Recognition
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The Gender Recognition Bill and Equality Law - Communist Party of Britain
Communist Party executive committee STATEMENT March 2023 1 The GRR Bill was passed by the Scottish Parliament on 22 December, 2022. The Bill reforms the 2004 Gender Recognition Act (GRA) for Scotland only. It changes the process for obtaining a gender recognition certificate (GRC) for anyone born or ‘ordinarily resident’ in Scotland. It aims to change the basis on which people in Scotland can chan
GitHub - vladmandic/human: Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gaze Tracking, Gesture Recognition
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はじめに AIは、人工知能という名の通り人間的な処理を行えるコンピュータです。音声認識(Speech to Text)が耳、音声合成(Text to Speech)が口だとしたら、目の機能となるのが画像認識(Image Recognition)です。今回からは、画像認識の活用状況を業界別に見ていきましょう。 画像認識の分類 画像認識について書かれているネット記事を見ると、判で押したように次の3種類に分類されると解説しています。 物体検出顔認識文字認識 でも、Object Detection(物体検出)と認識(Classification)で大別するならともかく、認識の中から顔と文字だけピックアップして並べているのはどうも違和感があります。顔認証はバイオメトリクスの1つで指紋や虹彩、網膜、静脈などと並ぶものですし、文字認識もバーコード、QRコードなどもあります。 実際、認識対象は幅広く、顔や
Siamese Neural Networks for One-shot Image Recognition - Qiita
最近、Few-shot learningの欲が高まっている@syunikuです。今さらSiamese Neural Networks for One-shot Image Recognition という論文を読んだので忘れないようにまとめておきたいと思います。 概要 この論文ではOne-shot Learningというタスクに対して、Deep metric learningの一手法であるSiamese Networkを適用することで当時のSOTA (State-of-the-Art)を達成した論文になります。現在の多くのFew-shot Learningの手法はこの手法に少なからず影響を受けていると思います。 One-shot Learning では、まず対象とするタスクについて話していきます。One-shot Learningはクラスに対してひとつのサンプルしか与えられていない状況を対象
face_recognition/README_Japanese.md at master · m-i-k-i/face_recognition
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Philosophy We strive to create an environment conducive to many different types of research across many different time scales and levels of risk. Learn more about our Philosophy Learn more
Photo by Jasmin Ne on UnsplashNER is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc. NER is used in many fields in Natural Language Processing (NLP), and it can help to answer
Benchmarking Quantized Mobile Speech Recognition Models with PyTorch Lightning and Grid
PyTorch Lightning enables you to rapidly train models while not worrying about boilerplate. While this makes training easier, in practice models are not trained for the sake of training models but rather for deploying to production applications. In this fourth and final part of the tutorial, we summarize our findings from the first three parts (Training a baseline model, Background on Quantization
This sample demonstrates how to compare multiple multi-class classifiers using the letter recognition dataset. ##Compare Multi-class Classifiers: Letter Recognition This sample demonstrates how to create multiclass classifiers and evaluate and compare the performance of multiple models. ##Data For this experiment, we use the letter image recognition data from the [UCI repository](http://archive.ic
GitHub - sindresorhus/awesome-whisper: 🔊 Awesome list for Whisper — an open-source AI-powered speech recognition system developed by OpenAI
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GitHub - mindee/doctr: docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.
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We’re shutting down the Face Recognition system on Facebook. People who’ve opted in will no longer be automatically recognized in photos and videos and we will delete more than a billion people’s individual facial recognition templates. This change will also impact Automatic Alt Text (AAT), which creates image descriptions for blind and visually-impaired people. After this change, AAT descriptions
Smart TVs implement a unique tracking approach called Automatic Content Recognition (ACR) to profile viewing activity of their users. ACR is a Shazam-like technology that works by periodically capturing the content displayed on a TV's screen and matching it against a content library to detect what content is being displayed at any given point in time. While prior research has investigated third-pa
Despite rapid progress in the recent past, current speech recognition systems still require labeled training data which limits this technology to a small fraction of the languages spoken around the globe. This paper describes wav2vec-U, short for wav2vec Unsupervised, a method to train speech recognition models without any labeled data. We leverage self-supervised speech representations to segment
Last month a controversial facial recognition company, Clearview AI, announced it had given its technology to the Ukrainian government. The BBC has been given evidence of how it is being used - in more than a thousand cases - to identify both the living and the dead. This story contains graphic descriptions that may be upsetting to some readers. A man lies motionless on the floor, his head tilted
Quickstart: Optical character recognition (OCR) - Azure AI services
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Handwriting Recognition with ML (An In-Depth Guide)
AIは実社会でどのように活用されているのか④ー画像認識(2)(Image Recognition)
Exploring Self-attention for Image Recognition
wav2vec Unsupervised: Speech recognition without supervision
Russia uses facial recognition to tackle virus
Advancing Instance-Level Recognition Research
AIは実社会でどのように活用されているのか③ー画像認識(Image Recognition)
Transformers for Image Recognition at Scale
Named Entity Recognition (NER) with BERT in Spark NLP
Compare Multi-class Classifiers: Letter recognition
An Update On Our Use of Face Recognition | Meta
Watching TV with the Second-Party: A First Look at Automatic Content Recognition Tracking in Smart TVs
Unsupervised Speech Recognition
How facial recognition is identifying the dead in Ukraine