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  • Lecture Collection | Convolutional Neural Networks for Visual Recognition (Spring 2017)

    Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving car...

      Lecture Collection | Convolutional Neural Networks for Visual Recognition (Spring 2017)
    • Deep Learning Image Recognition Using GPUs in Amazon ECS Docker Containers

      Update: it’s no longer necessary to copy the drivers into the runtime and expose volumes from the host. We’ve written up a “How To” on the the new process here: https://medium.com/@bfolkens/deep-learning-image-recognition-using-gpus-in-amazon-ecs-docker-containers-part-ii-56748701b116 Scaling up a web service was once a nightmare among DevOps. Provisioning and maintaining ‘N’ machines, handling fa

        Deep Learning Image Recognition Using GPUs in Amazon ECS Docker Containers
      • Image Recognition - TensorFlow

        TensorFlow Hub is a repository of pre-trained TensorFlow models. This tutorial demonstrates how to: Use models from TensorFlow Hub with tf.keras. Use an image classification model from TensorFlow Hub. Do simple transfer learning to fine-tune a model for your own image classes. Setup import numpy as np import time import PIL.Image as Image import matplotlib.pylab as plt import tensorflow as tf impo

          Image Recognition - TensorFlow
        • GitHub - justadudewhohacks/face-api.js: JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js

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            GitHub - justadudewhohacks/face-api.js: JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
          • VOSK Offline Speech Recognition API

            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. More to come. Works offlin

            • GitHub - nullpo-head/WSL-Hello-sudo: Let's sudo by face recognition of Windows Hello on Windows Subsystem for Linux (WSL). It runs on both WSL 1 and WSL 2. This is a PAM module for Linux on WSL.

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                GitHub - nullpo-head/WSL-Hello-sudo: Let's sudo by face recognition of Windows Hello on Windows Subsystem for Linux (WSL). It runs on both WSL 1 and WSL 2. This is a PAM module for Linux on WSL.
              • PimEyes: Face Recognition Search Engine and Reverse Image Search |

                Face Search Engine Reverse Image Search Upload photo and find out where images are published

                  PimEyes: Face Recognition Search Engine and Reverse Image Search |
                • Google で簡単に「顔」が検索できるようになる Firefox 拡張機能 | Google Image Type Recognition - Forgot the Milk.

                  Googleの イメージ検索 で顔写真を検索ができる機能が追加された件は ここ で紹介しましたが、URLをいじらなければならず、気軽に利用できるものではありませんでした。 今回紹介する Greasemonkey用のFirefoxエクステンションを導入すると、それらをプルダウンメニューから選択して簡単に利用することができるようになります。 導入後のスクリーンショット プルダウンから「Faces」を選択して検索しなおすと、顔に関するイメージを検索することができます。また、「News」を選択して検索しなおすと、ニュースに関するイメージを検索することができます。「All Image Type」はもちろん今まで通りの全ての画像が対象になります。 インストールはこちらからどうぞ。(画面右側の "Install this script" をクリック) http://userscripts.org/scr

                  • AudioTag.info | Free music recognition robot

                    Optimal duration is 15-45 sec. The robot analyzes up to 5 min from the beginning of audio. Read more...

                      AudioTag.info | Free music recognition robot
                    • GitHub - xuebinqin/U-2-Net: The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."

                      ** (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

                        GitHub - xuebinqin/U-2-Net: The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."
                      • GitHub - julius-speech/julius: Open-Source Large Vocabulary Continuous Speech Recognition Engine

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                          GitHub - julius-speech/julius: Open-Source Large Vocabulary Continuous Speech Recognition Engine
                        • This Mystery Photo Haunting Reddit Appears to Be Image Recognition Gone Very Weird

                          Take your next trip with Atlas Obscura! Our small-group adventures are inspired by our Atlas of the world's most fascinating places, the stories behind them, and the people who bring them to life. Visit Adventures

                            This Mystery Photo Haunting Reddit Appears to Be Image Recognition Gone Very Weird
                          • GitHub - PaddlePaddle/PaddleOCR: Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server,

                            🔥PaddleOCR 算法模型挑战赛 火热开启!报名时间1/15-3/31,30万元奖金池!快来一展身手吧😎! 🔨2023.11 发布 PP-ChatOCRv2: 一个SDK,覆盖20+高频应用场景,支持5种文本图像智能分析能力和部署,包括通用场景关键信息抽取(快递单、营业执照和机动车行驶证等)、复杂文档场景关键信息抽取(解决生僻字、特殊标点、多页pdf、表格等难点问题)、通用OCR、文档场景专用OCR、通用表格识别。针对垂类业务场景,也支持模型训练、微调和Prompt优化。 🔥2023.8.7 发布 PaddleOCR release/2.7 发布PP-OCRv4,提供mobile和server两种模型 PP-OCRv4-mobile:速度可比情况下,中文场景效果相比于PP-OCRv3再提升4.5%,英文场景提升10%,80语种多语言模型平均识别准确率提升8%以上 PP-OCRv

                              GitHub - PaddlePaddle/PaddleOCR: Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server,
                            • LookTel - Mobile Object Recognition and Remote Assistance Solutions for Visually Impaired Users

                              What is LookTel? LookTel is developing a suite of revolutionary assistive smartphone applications that bring the most powerful recognition technology of today to the aid of persons with low vision or blindness. This real-time recognition technology enables users to scan and instantly recognize objects such as packaged goods, soda cans, money, CDs, and landmarks like signs and store fronts. LookTel

                              • Sources: Apple is acquiring music recognition app Shazam | TechCrunch

                                Update: this story has now been confirmed. As Spotify continues to inch towards a public listing, Apple is making a move of its own to step up its game in music services. Sources tell us that the company is close to acquiring Shazam, the popular app that lets people identify any song, TV show, film or advert in seconds, by listening to an audio clip or (in the case of, say, an ad) a visual fragmen

                                  Sources: Apple is acquiring music recognition app Shazam | TechCrunch
                                • 2Captcha: Captcha Solving Service, reCAPTCHA Recognition and Bypass, Fast Auto Anti Captcha

                                  Fast online auto captcha solverOur team solves your CAPTCHA with high accuracy. To start using the service: RegisterImplement our APISend us your CAPTCHAsGet your answer as textIt’s quick and easy! 2Captcha provides low prices and high accuracy for your CAPTCHAs. Online statistics reCAPTCHA Bypass and Auto Solving Service2Captcha is best reCAPTCHA bypass serivce. Pay only for solved captchas. The

                                  • Visual and Face Recognition Tests on the Internet

                                    Feel like doing some more tests like these? Come to TestMyBrain.org, a new website devoted to web-based psychology experiments.

                                    • Deep Speech: Scaling up end-to-end speech recognition

                                      We present a state-of-the-art speech recognition system developed using end-to-end deep learning. Our architecture is significantly simpler than traditional speech systems, which rely on laboriously engineered processing pipelines; these traditional systems also tend to perform poorly when used in noisy environments. In contrast, our system does not need hand-designed components to model backgroun

                                      • The Ultimate Guide To Speech Recognition With Python – Real Python

                                        Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Speech Recognition With Python Have you ever wondered how to add speech recognition to your Python project? If so, then keep reading! It’s easier than you might think. Far from a being a fad, the overwhelming success of speech-enabled product

                                          The Ultimate Guide To Speech Recognition With Python – Real Python
                                        • Google contractors reportedly targeted homeless people for Pixel 4 facial recognition

                                          Tech/GoogleGoogle contractors reportedly targeted homeless people for Pixel 4 facial recognition Google contractors reportedly targeted homeless people for Pixel 4 facial recognition / They need facial scans of people with darker skin By Sean Hollister, a senior editor and founding member of The Verge who covers gadgets, games, and toys. He spent 15 years editing the likes of CNET, Gizmodo, and En

                                            Google contractors reportedly targeted homeless people for Pixel 4 facial recognition
                                          • Face recognition with OpenCV, Python, and deep learning - PyImageSearch

                                            Deep Learning dlib Face Applications Tutorials by Adrian Rosebrock on June 18, 2018 Last updated on December 30th, 2022 with content updates. In today’s blog post you are going to learn how to perform face recognition in both images and video streams using: OpenCVPythonDeep learning As we’ll see, the deep learning-based facial embeddings we’ll be using here today are both (1) highly accurate and (

                                              Face recognition with OpenCV, Python, and deep learning - PyImageSearch
                                            • Simple Digit Recognition OCR in OpenCV-Python

                                              Well, I decided to workout myself on my question to solve the above problem. What I wanted is to implement a simple OCR using KNearest or SVM features in OpenCV. And below is what I did and how. (it is just for learning how to use KNearest for simple OCR purposes). 1) My first question was about letter_recognition.data file that comes with OpenCV samples. I wanted to know what is inside that file.

                                                Simple Digit Recognition OCR in OpenCV-Python
                                              • [新機能] Amazon RekognitionでCelebrity Recognition(有名人認識機能)が出来るようになりました! | DevelopersIO

                                                はじめに 今日の新機能はこちら。 Easily recognize famous individuals and celebrities using Amazon Rekognition Amazon RekognitionでCelebrity Recognition(有名人認識機能)が出来るようになりました。映画やテレビ、政治、ビジネス、スポーツなどのジャンルにおける有名人を認識することができるようになったとのこと。 やってみた Amazon Rekognitionの管理コンソールにアクセスすると、Celebrity recognitionというリンクが増えています。 クリックするとデモ画面が表示されます。いきなりAmazonのCEOであるJeff Bezosが大写しにされるのでちょっとビビりますね。 もう1つのデモ画像はAmazon Web ServicesのCEO、Andy Jass

                                                  [新機能] Amazon RekognitionでCelebrity Recognition(有名人認識機能)が出来るようになりました! | DevelopersIO
                                                • Topic modeling survey on pattern recognition perspective - Bag of ML Words

                                                  トピックモデルのサーベイ講演したので貼っておきますね。 複数のパターン認識応用の立場でサーベイした話はたぶんないので価値あると思います。詳細版はPRMUの2015年12月予稿を入手(購入)してください。 さて、これを英語論文化しないといけないわけだが。 20151221 public from Katsuhiko Ishiguro www.slideshare.net

                                                    Topic modeling survey on pattern recognition perspective - Bag of ML Words
                                                  • Building a Real-Time Object Recognition App with Tensorflow and OpenCV

                                                    In this article, I will walk through the steps how you can easily build your own real-time object recognition application with Tensorflow’s (TF) new Object Detection API and OpenCV in Python 3 (specifically 3.5). The focus will be on the challenges that I faced when building it. You can find the full code on my repo. And here is also the app in action: Me trying to classify some random stuff on my

                                                      Building a Real-Time Object Recognition App with Tensorflow and OpenCV
                                                    • Face Recognition with OpenCV — OpenCV 2.4.13.7 documentation

                                                      Introduction¶ OpenCV (Open Source Computer Vision) is a popular computer vision library started by Intel in 1999. The cross-platform library sets its focus on real-time image processing and includes patent-free implementations of the latest computer vision algorithms. In 2008 Willow Garage took over support and OpenCV 2.3.1 now comes with a programming interface to C, C++, Python and Android. Open

                                                      • kaggle TensorFlow Speech Recognition Challengeの上位者のアプローチを紹介する(前編) - Qiita

                                                        kaggle TensorFlow Speech Recognition Challengeの上位者のアプローチを紹介する(前編)DeepLearning音声認識データサイエンスKaggleSpeechRecognition INTRODUCTION 今更ながらこちらのkaggleのコンペの上位者のアプローチを紹介します。 TensorFlow Speech Recognition Challenge tensorflowの名を冠していることから予想できるように、 google brainがorganizerです。 自分も一応は参加しておりました・・・。 長いので前編・後編に分けてポストいたします。 今回はコンペそのものと、アプローチの要素のうちタスク設計と特徴量について触れます。 このコンペについて コンペのタスクの内容 音声認識の中でも、いわゆる"keyword spotting" t

                                                          kaggle TensorFlow Speech Recognition Challengeの上位者のアプローチを紹介する(前編) - Qiita
                                                        • Zinnia: Online hand writing recognition system with machine learning

                                                          Zinnia: Online hand recognition system with machine learning [Japanese][English] Zinnia is a simple, customizable and portable online hand recognition system based on Support Vector Machines. Zinnia simply receives user pen strokes as a sequence of coordinate data and outputs n-best characters sorted by SVM confidence. To keep portability, Zinnia doesn't have any rendering functionality. In additi

                                                          • Activity Recognition Transition API による状況認識機能をすべてのデベロッパーに開放

                                                            .app 1 .dev 1 #11WeeksOfAndroid 13 #11WeeksOfAndroid Android TV 1 #Android11 3 #DevFest16 1 #DevFest17 1 #DevFest18 1 #DevFest19 1 #DevFest20 1 #DevFest21 1 #DevFest22 1 #DevFest23 1 #hack4jp 3 11 weeks of Android 2 A MESSAGE FROM OUR CEO 1 A/B Testing 1 A4A 4 Accelerator 6 Accessibility 1 accuracy 1 Actions on Google 16 Activation Atlas 1 address validation API 1 Addy Osmani 1 ADK 2 AdMob 32 Ads

                                                              Activity Recognition Transition API による状況認識機能をすべてのデベロッパーに開放
                                                            • 音声→テキスト変換のSpeech Recognition APIの使い方と、2017年4月におけるWatson、Google Cloud Speech APIとの違い

                                                              ※本稿は2017年4月12日の情報を元に作成しています。この記事内で使用している画面やコグニティブサービスの仕様は変更になっている場合があります。 本連載「認識系API活用入門」では、マイクロソフトのコグニティブサービスのAPIを用いて、「現在のコグニティブサービスでどのようなことができるのか」「どのようにして利用できるのか」「どの程度の精度なのか」を検証していきます。連載第1回の「Deep Learningの恩恵を手軽に活用できるコグニティブサービスとは」では、コグニティブサービスとは何かの概要とAPIを使うための準備の仕方を説明しました。 今回はSpeech Recognition APIを試します。 Speech Recognition APIとは Speech Recognition APIは、前回のText To Speech APIの逆で、音声データをAPIに渡すとその音声デー

                                                                音声→テキスト変換のSpeech Recognition APIの使い方と、2017年4月におけるWatson、Google Cloud Speech APIとの違い
                                                              • Announcing Google-Landmarks-v2: An Improved Dataset for Landmark Recognition & R

                                                                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

                                                                  Announcing Google-Landmarks-v2: An Improved Dataset for Landmark Recognition & R
                                                                • GitHub - KingOfBrian/VocalKit: Objective-C shim layer for Speech Recognition

                                                                  VocalKit I no longer advise using VocalKit, as a much better project, Open Ears has come out. http://www.politepix.com/openears/ VocalKit is a wrapper for available open source Speech related packages. It's goal is to ease the development of voice recognition solutions for the iPhone by providing a nice, simple Objective-C API. Currently VocalKit is in an Alpha version and just wraps Pocket Sphinx

                                                                    GitHub - KingOfBrian/VocalKit: Objective-C shim layer for Speech Recognition
                                                                  • Recognition Benchmark Images

                                                                    Revised set! In the first set which went online there were some errors. Most notably one subset being included twice. Also some transposed images. Tests on the old set are invalid. Henrik Stewénius and David Nistér The set consists of N groups of 4 images each. All the images are 640x480. If you use the dataset, please refer to: D. Nistér and H. Stewénius. Scalable recognition with a vocabul

                                                                    • Machine Learning is Fun Part 6: How to do Speech Recognition with Deep Learning

                                                                      Update: This article is part of a series. Check out the full series: Part 1, Part 2, Part 3, Part 4, Part 5, Part 6, Part 7 and Part 8! You can also read this article in 普通话 , 한국어, Tiếng Việt, فارسی or Русский. Giant update: I’ve written a new book based on these articles! It not only expands and updates all my articles, but it has tons of brand new content and lots of hands-on coding projects. Ch

                                                                        Machine Learning is Fun Part 6: How to do Speech Recognition with Deep Learning
                                                                      • How Disney uses PyTorch for animated character recognition

                                                                        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

                                                                          How Disney uses PyTorch for animated character recognition
                                                                        • Pittsburgh Pattern Recognition – Google Pittsburgh Pattern Recognition

                                                                          Pittsburgh Pattern Recognition has been acquired by Google, Inc. For media inquiries, please contact press@google.com.

                                                                          • [PDF] Real-Time Human Pose Recognition in Parts from Single Depth Images

                                                                              [PDF] Real-Time Human Pose Recognition in Parts from Single Depth Images
                                                                            • Announcing Google-Landmarks-v2: An Improved Dataset for Landmark Recognition & Retrieval

                                                                              Posted by Bingyi Cao and Tobias Weyand, Software Engineers, Google AI Last year we released Google-Landmarks, the largest world-wide landmark recognition dataset available at that time. In order to foster advancements in research on instance-level recognition (recognizing specific instances of objects, e.g. distinguishing Niagara Falls from just any waterfall) and image retrieval (matching a speci

                                                                                Announcing Google-Landmarks-v2: An Improved Dataset for Landmark Recognition & Retrieval
                                                                              • DeNA, MoT AI勉強会発表資料「顔認識と最近のArcFaceまわりと」 / Face Recognition & ArcFace papers

                                                                                DeNA, Mobility TechnologiesのAI勉強会で発表した資料です ・顔認識分野周りってどんな感じなの ・特に、最近のArcFaceまわりの手法どうなってきてるの 紹介論文: AdaptiveFace (CVPR’19) AdaCos (CVPR’19) (MV-ArcFace (AAAI’20)) CurricularFace (CVPR’20) GroupFace (CVPR’20) Sub-center ArcFace (ECCV’20) MagFace (CVPR’21) ElasticFace (CVPRW’22) AdaFace (CVPR’22)

                                                                                  DeNA, MoT AI勉強会発表資料「顔認識と最近のArcFaceまわりと」 / Face Recognition & ArcFace papers
                                                                                • The Modern History of Object Recognition — Infographic

                                                                                  Object Recognition has recently become one of the most exciting fields in computer vision and AI. The ability of immediately recognizing all the objects in a scene seems to be no longer a secret of evolution. With the development of Convolutional Neural Network architectures, backed by big training data and advanced computing technology, a computer now can surpass human performance in object recog

                                                                                    The Modern History of Object Recognition — Infographic