5 papers
Frozen but Not Always Accessible: A Representation Analysis of Genomic Language Models
Nirjhor Datta, Swakkhar Shatabda, M. Sohel Rahman
Genomic foundation models are increasingly reused as frozen feature extractors for downstream sequence prediction, offering a compute-efficient alternative to full fine-tuning. How…
Enlight: Fast Low-Light Image Enhancement via Multi-Objective Optimization and Shadow-Aware Refinement
Nirjhor Datta, M. Sohel Rahman
We present ENLIGHT, a fast and training free framework for low-light image enhancement based on direct optimization of a perceptual objective. Unlike deep learning approaches that…
Erase to Retain: Low Rank Adaptation Guided Selective Unlearning in Medical Segmentation Networks
Nirjhor Datta, Md. Golam Rabiul Alam
The ability to selectively remove knowledge from medical segmentation networks is increasingly important for privacy compliance, ethical deployment, and continual dataset revision.…
Embedding Is (Almost) All You Need: Retrieval-Augmented Inference for Generalizable Genomic Prediction Tasks
Nirjhor Datta, Swakkhar Shatabda, M Sohel Rahman
Large pre-trained DNA language models such as DNABERT-2, Nucleotide Transformer, and HyenaDNA have demonstrated strong performance on various genomic benchmarks. However, most appl…
Entropy-Driven Genetic Optimization for Deep-Feature-Guided Low-Light Image Enhancement
Nirjhor Datta, Afroza Akther, M. Sohel Rahman
Image enhancement methods often prioritize pixel level information, overlooking the semantic features. We propose a novel, unsupervised, fuzzy-inspired image enhancement framework…