Assessing the Robustness of Deep Learning-Based Gait Recognition Systems Against Adversarial Attacks-Reference-Cited by-同舟云学术

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Assessing the Robustness of Deep Learning-Based Gait Recognition Systems Against Adversarial Attacks

Published:2024-04-18 Issue: Volume:18 Page:1-8
ISSN:
Container-title:Proceedings of the 7th International Conference on Networking, Intelligent Systems and Security
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Author:

Saoudi El Mehdi¹^ORCID,Jai Andaloussi Said¹^ORCID,Jaafari Jaafar²^ORCID

Affiliation:

1. Department of Mathematics and Computer Science, Faculty Of Sciences Ain Chock Hassan 2 University Of Casablanca Casablanca Morocco, Morocco

2. Department of Computer Science, Sciences and technologies Faculty Hassan 2 University Of Casablanca Mohammedia Morocco, Morocco

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3659677.3659824

Reference36 articles.

1. Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey

2. Advances in Adversarial Attacks and Defenses in Computer Vision: A Survey

3. M Amanulla Khan and SMH Sithi Shameem Fathima. 2023. Multi gait recognition using Clustering based Faster Regions-Convolutional Neural Network. Journal of Intelligent & Fuzzy SystemsPreprint (2023), 1–10.

4. Convolutional Bi-LSTM Based Human Gait Recognition Using Video Sequences

5. Radar-Based Human Gait Recognition Using Dual-Channel Deep Convolutional Neural Network

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