5 papers
Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach
Wasimul Karim, Nur Mohammad Fahad, Abdul Hasib Siddique +4
Accurate segmentation of electrolyzer materials is essential for automated disassembly, sustainable recycling, and circular manufacturing in hydrogen technologies. However, this ta…
BioAutoML-NAS: An End-to-End AutoML Framework for Multimodal Insect Classification via Neural Architecture Search on Large-Scale Biodiversity Data
Arefin Ittesafun Abian, Debopom Sutradhar, Md Rafi Ur Rashid +5
Insect classification is important for agricultural management and ecological research, as it directly affects crop health and production. However, this task remains challenging du…
DeepAgent: A Dual Stream Multi Agent Fusion for Robust Multimodal Deepfake Detection
Sayeem Been Zaman, Wasimul Karim, Arefin Ittesafun Abian +4
The increasing use of synthetic media, particularly deepfakes, is an emerging challenge for digital content verification. Although recent studies use both audio and visual informat…
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…
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…