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Facial recognition software at a US airport Automatic ticket gate with face recognition system in Osaka Metro Morinomiya Station. A facial recognition system [1] is a technology potentially capable of matching a human face from a digital image or a video frame against a database of faces.
Although palm vein recognition, iris recognition and face recognition have been implemented in schools, finger scanning is by far the most commonly used technology in the U.S. education market. [ 3 ] In the UK, primarily the type of biometric employed is a fingerprint scan or thumbprint scan, but vein and iris scanning systems are also in use.
OMR – for marks recognition [4] OBR – for barcodes recognition [5] BCR – for bar code recognition [6] DLR – for document layer recognition [citation needed] These basic technologies allow extracting information from paper documents for further processing in the enterprise information systems such as ERP, CRM, and others. [citation needed]
The Face system uses class-based scatter matrices to calculate features for recognition, and the Palm Vein acts as an unbreakable cryptographic key, ensuring only the correct user can access the system. The cancelable Biometrics concept allows biometric traits to be altered slightly to ensure privacy and avoid theft.
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.
Face recognition, classification 2011 [111] Zhao, G. et al. BU-3DFE neutral face, and 6 expressions: anger, happiness, sadness, surprise, disgust, fear (4 levels). 3D images extracted. None. 2500 Images, text Facial expression recognition, classification 2006 [112] Binghamton University: Face Recognition Grand Challenge Dataset
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