■イベント :自然言語処理勉強会 https://sansan.connpass.com/event/190157/ ■登壇概要 タイトル:実務で使う固有表現抽出 発表者: DSOC R&D研究員 高橋 寛治 ▼Twitter https://twitter.com/SansanRandD
Optical character recognition for Japanese text, with the main focus being Japanese manga. It uses a custom end-to-end model built with Transformers' Vision Encoder Decoder framework. Manga OCR can be used as a general purpose printed Japanese OCR, but its main goal was to provide a high quality text recognition, robust against various scenarios specific to manga: both vertical and horizontal text
iOS 13以降で、待望だった「文字認識」機能が使えるようになりました。カメラなどで撮影した画像内にある文字を読み取る [1] ことができます。 iOS 9からあった「文字検出」との違い 文字認識は、Visionフレームワークの一機能として追加されました。 一方、Core ImageのCIDetectorというクラスでは、CIDetectorTypeTextというタイプを指定でき、テキストを検出することができます。 このCIDetectorTypeTextやCIFeatureTypeTextはiOS 9からあるものです。 しかしこちらは文字の「領域」を検出する機能です。何が書いてあるか、までは認識できませんでした。 そこで今まではTesseract[2]というオープンソースのOCRエンジンや、SwiftOCR[3]という(おそらく個人がメンテしている)OSSしか選択肢がなかったのですが、つ
Vosk is an offline open source speech recognition toolkit. It enables speech recognition for 20+ languages and dialects - English, Indian English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish, Vietnamese, Italian, Dutch, Catalan, Arabic, Greek, Farsi, Filipino, Ukrainian, Kazakh, Swedish, Japanese, Esperanto, Hindi, Czech, Polish. More to come. Vosk models are small (50 Mb) but p
РУС 中文 Vosk is a speech recognition toolkit. The best things in Vosk are: Supports 20+ languages and dialects - English, Indian English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish, Vietnamese, Italian, Dutch, Catalan, Arabic, Greek, Farsi, Filipino, Ukrainian, Kazakh, Swedish, Japanese, Esperanto, Hindi, Czech, Polish, Uzbek, Korean, Breton, Gujarati, Tajik. More to come. Works
** (2022-Aug.-24) ** We are glad to announce that our U2-Net published in Pattern Recognition has been awarded the 2020 Pattern Recognition BEST PAPER AWARD !!! ** (2022-Aug.-17) ** Our U2-Net models are now available on PlayTorch, where you can build your own demo and run it on your Android/iOS phone. Try out this demo on and bring your ideas about U2-Net to truth in minutes! ** (2022-Jul.-5)** O
Authors: Miquel Àngel Farré, Anthony Accardo, Marc Junyent, Monica Alfaro, Cesc Guitart at Disney Disney’s Content GenomeThe long and incremental evolution of the media industry, from a traditional broadcast and home video model, to a more mixed model with increasingly digitally-accessible content, has accelerated the use of machine learning and artificial intelligence (AI). Advancing the implemen
Amplify+Angular+Recognitionを使って画像からテキストを読み取るアプリケーションをサクッと作ってみる どうも!大阪オフィスの西村祐二です。 今回はAngularとAmplifyとRecognitionを使って画像からテキストを読み取るアプリケーションを作ってみたいと思います。 ゴールとなるアプリケーションは下記になります。 文字が含まれる画像をアップロードするとバックエンドのRecognitionのAPIをコールし、画像からテキストを抽出して表示するというアプリケーションです。 作ってみる 環境 aws-amplify: 2.2.2 amplify cli: 4.12.0 Angular CLI: 8.3.23 Node: 12.13.0 OS: darwin x64 Angular: 8.2.14 ... animations, common, compiler,
このように、複数追加もできるようです。 Noodl1.3ではこのような処理はif文で書いていました。2.0のほうがスッキリかけそうですね。 change:function inputの値のどれかが変更されたときに実行される。 このプロジェクトのJavascriptノードの中身 サンプルでは、ラーメンをタップしたときにmySignalにtrueのシグナルを送り、音声認識を実行させています。 define({ // The input ports of the Javascript node, name of input and type inputs:{ // ExampleInput:'number', // Available types are 'number', 'string', 'boolean', 'color' and 'signal', mySignal:'signal'
The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site. The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.
Image recognition (i.e. classifying what object is shown in an image) is a core task in computer vision, as it enables various downstream applications (automatically tagging photos, assisting visually impaired people, etc.), and has become a standard task on which to benchmark machine learning (ML) algorithms. Deep learning (DL) algorithms have, over the past decade, emerged as the most competitiv
This repository provides fast automatic speech recognition (70x realtime with large-v2) with word-level timestamps and speaker diarization. ⚡️ Batched inference for 70x realtime transcription using whisper large-v2 🪶 faster-whisper backend, requires <8GB gpu memory for large-v2 with beam_size=5 🎯 Accurate word-level timestamps using wav2vec2 alignment 👯♂️ Multispeaker ASR using speaker diariza
Batch normalization is a key component of most image classification models, but it has many undesirable properties stemming from its dependence on the batch size and interactions between examples. Although recent work has succeeded in training deep ResNets without normalization layers, these models do not match the test accuracies of the best batch-normalized networks, and are often unstable for l
Large Language Models and Multimodal Models New Llama 3.1 Support (2024-07-23) The NeMo Framework now supports training and customizing the Llama 3.1 collection of LLMs from Meta. Accelerate your Generative AI Distributed Training Workloads with the NVIDIA NeMo Framework on Amazon EKS (2024-07-16) NVIDIA NeMo Framework now runs distributed training workloads on an Amazon Elastic Kubernetes Service
レコードやオブジェクトを教師あり学習・教師なし学習や検索エンジンで 名寄せ(Entity Recognition・Deduplication)するときに、それぞれのフィールドから特徴量を抜き出す必要があります。 意外とまとまって言及しているリファレンスは少ないので、 特に文字列のフィールドでよく使われる特徴量を上げてみました。 データベースのブロッキングに使われるものも含まれます。 特徴量の種類 分類は独自の基準に基づきます。 Token 固有表現 音素 分散表現/次元圧縮 検索スコア 距離・擬似距離 (レコードのペアの場合) 各特徴量の概要 1. Token 文字列から、さらに小さい構成単位を抽出します。 ただし、次元が大きいsparse matrixになるため、機械学習やクラスタリングで用いるには次元に対して大量のデータが必要か、工夫が必要です。 character ngram ご存じ
While the Transformer architecture has become the de-facto standard for natural language processing tasks, its applications to computer vision remain limited. In vision, attention is either applied in conjunction with convolutional networks, or used to replace certain components of convolutional networks while keeping their overall structure in place. We show that this reliance on CNNs is not nece
iOS 14 comes with support for Sound Recognition in Accessibility. Your phone can now listen for specific sounds – a baby crying, smoke alarm, water running, etc. – and notify you. Amazing feature for all kinds of users – inclusivity at its best. #WWDC2020 pic.twitter.com/3hIL8JuTyB— Federico Viticci (@viticci) June 23, 2020
Correction: An earlier version of this story incorrectly stated that XRVision facial recognition software identified Antifa members among rioters who stormed the Capitol Wednesday. XRVision did not identify any Antifa members. The Washington Times apologizes to XRVision for the error. Facial recognition software has identified neo-Nazis and other extremists as participants in Wednesday’s assault o
PrefaceThe Simple Transformers library was conceived to make Transformer models easy to use. Transformers are incredibly powerful (not to mention huge) deep learning models which have been hugely successful at tackling a wide variety of Natural Language Processing tasks. Simple Transformers enabled the application of Transformer models to Sequence Classification tasks (binary classification initia
Review Open access Published: 31 January 2019 Recognition of aerosol transmission of infectious agents: a commentary Raymond Tellier1, Yuguo Li2, Benjamin J. Cowling3 & …Julian W. Tang4,5 Show authors BMC Infectious Diseases volume 19, Article number: 101 (2019) Cite this article Although short-range large-droplet transmission is possible for most respiratory infectious agents, deciding on whether
はじめまして!エンジニアのUemaです。 近年では、スマホのロックの解除や入館時の認証など様々なことに顔認識の技術が使われています。 顔認識を利用するには機械学習、画像処理や数学などの様々な知識が必要で学習コストがかかり、顔認識を使ってアプリケーションを作ってみたいと考えている人もなかなか手が出ないと思います。 そんな人に朗報です! 手軽に顔認識を行えるface-recognitionというPythonライブラリが存在します! 今回は顔認識の入り口として、face-recognitionを実際に使ってみたいと思います。 face-recognitionとは Pythonコードやコマンドラインで手軽に顔を検出・認識することができるライブラリです。face-recognitionの顔認識モデルは99%の正解率を記録しているそうです。 インストール(mac) Pythonとhomebrewがイン
Word2vec for audio quantizes phonemes, transforms, GAN trains on text and audio from Facebook AI. JS disabled! Watch Wav2vec: Semi-supervised and Unsupervised Speech Recognition on Youtube Watch video "Wav2vec: Semi-supervised and Unsupervised Speech Recognition" Wav2vec is fascinating in that it combines several neural network architectures and methods: CNN, transformer, quantization, and GAN tra
Did this help? Hosting Detexify costs money and if it helps you may consider helping to pay the hosting bill. Want a Mac app? Lucky you. The Mac app is finally stable enough. See how it works on Vimeo. Download the latest version here. Restriction: In addition to the LaTeX command the unlicensed version will copy a reminder to purchase a license to the clipboard when you select a symbol. You can p
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The Swedish DPA has fined a municipality 200 000 SEK (approximately 20 000 euros) for using facial recognition technology to monitor the attendance of students in school. A school in northern Sweden has conducted a pilot using facial recognition to keep track of students’ attendance in school. The test run was conducted in one school class for a limited period of time. The Swedish DPA concluded th
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