Abdul Rehman

Advanced machine learning approach using Kolmogorov-Arnold Networks (KANs) and comparison with RSM for optimization of biodiesel yield from palm based waste cooking oil

Abdul Rehman, Zhang Yunhe, Ding Zhou, Fayaz Hussain, Luqman Razzaq, Meor Faisal Zulkifli, et al.

From Triggers to Emotions: A CPM-Grounded Appraisal Multi-Agent for Dynamic Emotional Evolution in Persona-Based Dialogue

Jingyao Cai, Shuaijun Liu, Abdul Rehman, Yutong Guo, Qin Tian, Thomas Dolby, et al.

Large Language Models (LLMs) have substantially advanced persona-based dialogue agents for emotion-sensitive role simulation in healthcare, education, counseling, customer service, and interactive storytelling. However, two related lines of work leave a key gap. Persona-based dia…Read more

Learning Structurally Consistent Representations for Multi-View Radar Semantic Segmentation

Ali Zia, Muhammad Umer Ramzan, Abdelwahed Khamis, Usman Ali, Abdul Rehman

Radar sensors provide reliable perception under adverse weather and lighting conditions, but their sparse, noisy, and weakly semantic measurements make dense semantic segmentation challenging. Most existing radar segmentation methods rely on grid-based encodings and pairwise inte…Read more

Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation

Ali Zia, Usman Ali, Abdul Rehman, Umer Ramzan, Kang Han, Muhammad Faheem, et al.

Test-time adaptation (TTA) has emerged as a promising paradigm for mitigating distribution shifts in deep models. However, existing TTA approaches for anomaly segmentation remain limited by their reliance on pixel-level heuristics, such as confidence thresholding or entropy minim…Read more