Masked face recognition using deep learning: A review
A large number of intelligent models for masked face recognition (MFR) has been recently
presented and applied in various fields, such as masked face tracking for people safety or …
presented and applied in various fields, such as masked face tracking for people safety or …
A survey of face recognition techniques under occlusion
The limited capacity to recognise faces under occlusions is a long‐standing problem that
presents a unique challenge for face recognition systems and even humans. The problem …
presents a unique challenge for face recognition systems and even humans. The problem …
Partial person re-identification
We address a new partial person re-identification (re-id) problem, where only a partial
observation of a person is available for matching across different non-overlapping camera …
observation of a person is available for matching across different non-overlapping camera …
Deep convolutional neural networks for thermal infrared object tracking
Unlike the visual object tracking, thermal infrared object tracking can track a target object in
total darkness. Therefore, it has broad applications, such as in rescue and video …
total darkness. Therefore, it has broad applications, such as in rescue and video …
Joint sparse principal component analysis
Principal component analysis (PCA) is widely used in dimensionality reduction. A lot of
variants of PCA have been proposed to improve the robustness of the algorithm. However …
variants of PCA have been proposed to improve the robustness of the algorithm. However …
A comprehensive analysis of deep learning based representation for face recognition
M Mehdipour Ghazi… - Proceedings of the IEEE …, 2016 - cv-foundation.org
Deep learning based approaches have been dominating the face recognition field due to
the significant performance improvement they have provided on the challenging wild …
the significant performance improvement they have provided on the challenging wild …
Beyond the sparsity-based target detector: A hybrid sparsity and statistics-based detector for hyperspectral images
Hyperspectral images provide great potential for target detection, however, new challenges
are also introduced for hyperspectral target detection, resulting that hyperspectral target …
are also introduced for hyperspectral target detection, resulting that hyperspectral target …
Deep feature augmentation for occluded image classification
F Cen, X Zhao, W Li, G Wang - Pattern Recognition, 2021 - Elsevier
Due to the difficulty in acquiring massive task-specific occluded images, the classification of
occluded images with deep convolutional neural networks (CNNs) remains highly …
occluded images with deep convolutional neural networks (CNNs) remains highly …
COVID 19: Identification of Masked Face using CNN Architecture
Tackling with the Covid-19 pandemic has been a grueling task from the day one of its rise.
To prevent the spread of the virus, one of the major steps taken by governments of the world …
To prevent the spread of the virus, one of the major steps taken by governments of the world …
Techniques and challenges of face recognition: A critical review
S Singh, S Prasad - Procedia computer science, 2018 - Elsevier
A lot of researches are going on since last two decades for object recognition, shape
matching, and pattern recognition in the field of computer vision. Face recognition is one of …
matching, and pattern recognition in the field of computer vision. Face recognition is one of …