3 citations · 3 across the 10 of their papers we have counts for
10 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…
A physics-informed, behavior-aware digital twin for robust multimodal forecasting of core body temperature in precision livestock farming
Riasad Alvi, Mohaimenul Azam Khan Raiaan, Sadia Sultana Chowa +6
Precision livestock farming requires accurate and timely heat stress prediction to ensure animal welfare and optimize farm management. This study presents a physics-informed digita…
Learning to Weigh Waste: A Physics-Informed Multimodal Fusion Framework and Large-Scale Dataset for Commercial and Industrial Applications
Md. Adnanul Islam, Wasimul Karim, Md Mahbub Alam +7
Accurate weight estimation of commercial and industrial waste is important for efficient operations, yet image-based estimation remains difficult because similar-looking objects ma…
A Source-Free Approach for Domain Adaptation via Multiview Image Transformation and Latent Space Consistency
Debopom Sutradhar, Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan +2
Domain adaptation (DA) addresses the challenge of transferring knowledge from a source domain to a target domain where image data distributions may differ. Existing DA methods ofte…
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…
Mitigating hallucinations in healthcare LLMs with granular fact-checking and domain-specific adaptation
Musarrat Zeba, Abdullah Al Mamun, Kishoar Jahan Tithee +8
In healthcare, it is essential for any Large Language Model (LLM)-generated output to be reliable and accurate, particularly in cases involving decision-making and patient safety.…
Generative Artificial Intelligence in Bioinformatics: A Systematic Review of Models, Applications, and Methodological Advances
Wasimul Karim, Riasad Alvi, Sayeem Been Zaman +7
Generative artificial intelligence (GenAI) is transforming bioinformatics by advancing genomics, proteomics, transcriptomics, structural biology, and drug discovery. Following the…
ARIONet: An Advanced Self-supervised Contrastive Representation Network for Birdsong Classification and Future Frame Prediction
Md. Abdur Rahman, Selvarajah Thuseethan, Kheng Cher Yeo +2
Automated birdsong classification is essential for advancing ecological monitoring and biodiversity studies. Despite recent progress, existing methods often depend heavily on label…
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…
CLAIRE: A Dual Encoder Network with RIFT Loss and Phi-3 Small Language Model Based Interpretability for Cross-Modality Synthetic Aperture Radar and Optical Land Cover Segmentation
Debopom Sutradhar, Arefin Ittesafun Abian, Mohaimenul Azam Khan Raiaan +3
Accurate land cover classification from satellite imagery is crucial in environmental monitoring and sustainable resource management. However, it remains challenging due to the com…