Al-Andoli, Mohammed Nasser and Tan, Shing Chiang and Sim, Kok Swee and Goh, Pey Yun and Lim, Chee Peng (2024) A Framework for Robust Deep Learning Models Against Adversarial Attacks Based on a Protection Layer Approach. IEEE Access. p. 1. ISSN 2169-3536

Abuhoureyah, Fahd and Wong, Yan Chiew and Mohd Isira, Ahmad Sadhiqin and Al-Andoli, Mohammed Nasser (2023) Free device location independent WiFi‐based localisation using received signal strength indicator and channel state information. IET Wireless Sensor Systems. ISSN 2043-6386

Al-Andoli, Mohammed Nasser and Sim, Kok Swee and Tan, Shing Chiang and Goh, Pey Yun and Lim, Chee Peng (2023) An Ensemble-Based Parallel Deep Learning Classifier With PSO-BP Optimization for Malware Detection. IEEE Access, 11. pp. 76330-76346. ISSN 2169-3536

Al-Andoli, Mohammed Nasser and Tan, Shing Chiang and Sim, Kok Swee and Seera, Manjeevan and Lim, Chee Peng (2023) A Parallel Ensemble Learning Model for Fault Detection and Diagnosis of Industrial Machinery. IEEE Access, 11. pp. 39866-39878. ISSN 2169-3536

Sim, Kok Swee and Tan, Shing Chiang and Al-Andoli, Mohammed Nasser and Seera, Manjeevan and Lim, Chee Peng (2023) A Parallel Ensemble Learning Model for Fault Detection and Diagnosis of Industrial Machinery. IEEE Access, 11. pp. 39866-39878. ISSN 2169-3536

Al-Andoli, Mohammed Nasser and Tan, Shing Chiang and Sim, Kok Swee and Goh, Pey Yun and Lim, Chee Peng (2023) An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection. Journal of Intelligent & Fuzzy Systems, 44 (6). pp. 10477-10493. ISSN 1064-1246

Al-Andoli, Mohammed Nasser and Tan, Shing Chiang and Sim, Kok Swee and Lim, Chee Peng and Goh, Pey Yun (2022) Parallel Deep Learning with a hybrid BP-PSO framework for feature extraction and malware classification. Applied Soft Computing, 131. p. 109756. ISSN 1568-4946

Al-Andoli, Mohammed Nasser and Tan, Shing Chiang and Cheah, Wooi Ping and Tan, Sin Yin (2021) A Review on Community Detection in Large Complex Networks from Conventional to Deep Learning Methods: A Call for the Use of Parallel Meta-Heuristic Algorithms. IEEE Access, 9. pp. 96501-96527. ISSN 2169-3536