most citedMultilinear subspace learning for person re-identification based fusion of high order tensor features

21 citations · 21 across the 1 of their papers we have counts for

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5 papers

cs.CV202521 cited

Multilinear subspace learning for person re-identification based fusion of high order tensor features

Ammar Chouchane, Mohcene Bessaoudi, Hamza Kheddar +3

Video surveillance image analysis and processing is a challenging field in computer vision, with one of its most difficult tasks being Person Re-Identification (PRe-ID). PRe-ID aim…

cs.CV2023

A Powerful Face Preprocessing For Robust Kinship Verification based Tensor Analyses

Ammar chouchane, Mohcene Bessaoudi, Abdelmalik Ouamane

Kinship verification using facial photographs captured in the wild is difficult area of research in the science of computer vision. It might be used for a variety of applications,…

cs.CV2023

Enhancing Person Re-Identification through Tensor Feature Fusion

Akram Abderraouf Gharbi, Ammar Chouchane, Mohcene Bessaoudi +2

In this paper, we present a novel person reidentification (PRe-ID) system that based on tensor feature representation and multilinear subspace learning. Our approach utilizes pretr…

cs.CV2023

Fusion of Deep and Shallow Features for Face Kinship Verification

Belabbaci El Ouanas, Khammari Mohammed, Chouchane Ammar +3

Kinship verification from face images is a novel and formidable challenge in the realms of pattern recognition and computer vision. This work makes notable contributions by incorpo…

cs.CV2023

Enhancing Kinship Verification through Multiscale Retinex and Combined Deep-Shallow features

El Ouanas Belabbaci, Mohammed Khammari, Ammar Chouchane +5

The challenge of kinship verification from facial images represents a cutting-edge and formidable frontier in the realms of pattern recognition and computer vision. This area of st…