HGRBOL2: Human gait recognition for biometric application using Bayesian optimization and extreme learning machine-Reference-Cited by-同舟云学术

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HGRBOL2: Human gait recognition for biometric application using Bayesian optimization and extreme learning machine

Published:2023-06 Issue: Volume:143 Page:337-348
ISSN:0167-739X
Container-title:Future Generation Computer Systems
language:en
Short-container-title:Future Generation Computer Systems

Author:

Khan Muhammad Attique,Arshad Habiba,Khan Wazir Zada,Alhaisoni Majed,Tariq Usman,Hussein Hany S.,Alshazly Hammam,Osman Lobna,Elashry Ahmed

Funder

Deanship of Scientific Research, King Faisal University

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference49 articles.

1. Human gait recognition subject to different covariate factors in a multi-view environment;Asif;Results Eng.,2022

2. A comprehensive survey on deep gait recognition: Algorithms, datasets and challenges;Shen,2022

3. Pedestrian and animal recognition using doppler radar signature and deep learning;Buchman;Sensors,2022

4. CASIA-E: A large comprehensive dataset for gait recognition;Song;IEEE Trans. Pattern Anal. Mach. Intell.,2022

5. An adaptive multi-level quantization-based reinforcement learning model for enhancing UAV landing on moving targets;Abo Mosali;Sustainability,2022

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4. GaitSTAR: Spatial–Temporal Attention-Based Feature-Reweighting Architecture for Human Gait Recognition;Mathematics;2024-08-08

5. Enhancing gait recognition by multimodal fusion of mobilenetv1 and xception features via PCA for OaA-SVM classification;Scientific Reports;2024-07-26

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