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For further details check the project's GitHub repository or the Hugging Face ... vulnerabilities that is free to search, use, and incorporate into products and ...
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]
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]
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.
CMU Sphinx, a group of speech recognition systems developed at Carnegie Mellon University. [67] DeepSpeech, an open-source Speech-To-Text engine based on Baidu's deep speech research paper. [68] Whisper, an open-source speech recognition system developed at OpenAI. [69]
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.
Face recognition, which recently has become one of the most popular research areas of pattern recognition, copes with identification or verification of a person by their digital images. [ 68 ] Hierarchical ensembles based on Gabor Fisher classifier and independent component analysis preprocessing techniques are some of the earliest ensembles ...
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.