36 citations · 66 across the 8 of their papers we have counts for
8 papers
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…
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…
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…
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…
Improving ICD coding using Chapter based Named Entities and Attentional Models
Abhijith R. Beeravolu, Mirjam Jonkman, Sami Azam +1
Recent advancements in natural language processing (NLP) have led to automation in various domains. However, clinical NLP often relies on benchmark datasets that may not reflect re…
Methods to Measure the Broncho-Arterial Ratio and Wall Thickness in the Right Lower Lobe for Defining Radiographic Reversibility of Bronchiectasis
Abhijith R. Beeravolu, Ian Brent Masters, Mirjam Jonkman +9
The diagnosis of bronchiectasis requires measuring abnormal bronchial dilation. It is confirmed using a chest CT scan, where the key feature is an increased broncho-arterial ratio…
EWasteNet: A Two-Stream Data Efficient Image Transformer Approach for E-Waste Classification
Niful Islam, Md. Mehedi Hasan Jony, Emam Hasan +3
Improper disposal of e-waste poses global environmental and health risks, raising serious concerns. The accurate classification of e-waste images is critical for efficient manageme…