most citedMitigating hallucinations in healthcare LLMs with granular fact-checking and domain-specific adaptation

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cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

PPORLD-EDNetLDCT: A Proximal Policy Optimization-Based Reinforcement Learning Framework for Adaptive Low-Dose CT Denoising

Debopom Sutradhar, Ripon Kumar Debnath, Mohaimenul Azam Khan Raiaan +3

Low-dose computed tomography (LDCT) is critical for minimizing radiation exposure, but it often leads to increased noise and reduced image quality. Traditional denoising methods, s…

cs.CV2025

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…