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Benchmarking deep learning techniques for face recognition
Abstract Recent progresses in Convolutional Neural Networks (CNNs) and GPUs have
greatly advanced the state-of-the-art performance for face recognition. However, training …
greatly advanced the state-of-the-art performance for face recognition. However, training …
A novel multi-feature joint learning method for fast polarimetric SAR terrain classification
J Shi, H **, X Li - IEEE Access, 2020 - ieeexplore.ieee.org
Polarimetric synthetic aperture radar (PolSAR) image classification is one of the most
important study areas for PolSAR image processing. Many kinds of PolSAR features can be …
important study areas for PolSAR image processing. Many kinds of PolSAR features can be …
Deep learning vs hand-crafted features for face recognition under uncontrolled conditions
Facial recognition in degraded conditions has become a very active and widely used area in
several fields such as video surveillance and access control. Indeed, the presence of facial …
several fields such as video surveillance and access control. Indeed, the presence of facial …
Dictionary based Bayesian Classifier Learning
F Shafait - Journal of Computing & Biomedical Informatics, 2023 - jcbi.org
Dictionary and Classifier learning with discriminatory and joint behavior is a considerably
effective area in ML research being applied particularly for face recognition, action …
effective area in ML research being applied particularly for face recognition, action …
[LIBRO][B] Face Recognition with Attention Mechanisms
Q Wang - 2022 - search.proquest.com
Face recognition has been widely used in people's daily lives due to its contactless process
and high accuracy. Existing works can be divided into two categories: global and local …
and high accuracy. Existing works can be divided into two categories: global and local …