1 citations · 1 across the 1 of their papers we have counts for
5 papers
A fine-grained attention and geometric correspondence model for musculoskeletal risk classification in athletes using multimodal visual and skeletal features
Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan, Tamanna Shermin +3
Musculoskeletal disorders pose significant risks to athletes, and early risk assessment is essential for prevention. However, most existing methods are designed for controlled sett…
WeCKD: Weakly-supervised Chained Distillation Network for Efficient Multimodal Medical Imaging
Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan, Sami Azam +3
Knowledge distillation (KD) has traditionally relied on a static teacher-student framework, where a large, well-trained teacher transfers knowledge to a single student model. Howev…
From Language to Action: A Review of Large Language Models as Autonomous Agents and Tool Users
Sadia Sultana Chowa, Riasad Alvi, Subhey Sadi Rahman +5
The pursuit of human-level artificial intelligence (AI) has significantly advanced the development of autonomous agents and Large Language Models (LLMs). LLMs are now widely utiliz…
HANS-Net: Hyperbolic Convolution and Adaptive Temporal Attention for Accurate and Generalizable Liver and Tumor Segmentation in CT Imaging
Arefin Ittesafun Abian, Ripon Kumar Debnath, Md. Abdur Rahman +5
Accurate liver and tumor segmentation on abdominal CT images is critical for reliable diagnosis and treatment planning, but remains challenging due to complex anatomical structures…
Hallucination to Truth: A Review of Fact-Checking and Factuality Evaluation in Large Language Models
Subhey Sadi Rahman, Md. Adnanul Islam, Md. Mahbub Alam +5
Large Language Models (LLMs) are trained on vast and diverse internet corpora that often include inaccurate or misleading content. Consequently, LLMs can generate misinformation, m…