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FaceNet is a facial recognition system developed by Florian Schroff, Dmitry Kalenichenko and James Philbina, a group of researchers affiliated with Google.The system was first presented at the 2015 IEEE Conference on Computer Vision and Pattern Recognition. [1]
Automatic face detection with OpenCV. Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. [1] Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene.
A convolutional neural network (CNN) is a regularized type of feed-forward neural network that learns features by itself via filter (or kernel) optimization. This type of deep learning network has been applied to process and make predictions from many different types of data including text, images and audio. [1]
Face recognition has been leveraged as a form of biometric authentication for various computing platforms and devices; [37] Android 4.0 "Ice Cream Sandwich" added facial recognition using a smartphone's front camera as a means of unlocking devices, [66] [67] while Microsoft introduced face recognition login to its Xbox 360 video game console ...
Apache Lucene, a high-performance, full-featured text search engine library written entirely in Java. [49] Apache OpenNLP, a machine learning based toolkit for the processing of natural language text. It supports the most common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking and ...
A Tutorial on Face Recognition Using Eigenfaces and Distance Classifiers; Matlab example code for eigenfaces; OpenCV + C++Builder6 implementation of PCA; Java applet demonstration of eigenfaces Archived 2011-11-01 at the Wayback Machine; Introduction to eigenfaces; Face Recognition Function in OpenCV; Eigenface-based Facial Expression ...
DeepFace is a deep learning facial recognition system created by a research group at Facebook.It identifies human faces in digital images. The program employs a nine-layer neural network with over 120 million connection weights and was trained on four million images uploaded by Facebook users.
The Viola–Jones object detection framework is a machine learning object detection framework proposed in 2001 by Paul Viola and Michael Jones. [1] [2] It was motivated primarily by the problem of face detection, although it can be adapted to the detection of other object classes.