9 papers
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…
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…
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.…
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…
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…