Machine learning approach for segmenting glands in colon histology images using local intensity and texture features. - Rupali Khatun; Soumick Chatterjee (CoRR, 2019)

Uncertainty Modeling and Deep Learning Applied to Food Image Analysis. - Eduardo Aguilar 001; Bhalaji Nagarajan; Rupali Khatun; Marc Bolaños; Petia Radeva (BIOSTEC, 2020)

Uncertainty-Aware Data Augmentation for Food Recognition. - Eduardo Aguilar 001; Bhalaji Nagarajan; Rupali Khatun; Marc Bolaños; Petia Radeva (ICPR, 2020)

Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray Images. - Soumick Chatterjee; Fatima Saad; Chompunuch Sarasaen; Suhita Ghosh; Rupali Khatun; Petia Radeva; Georg Rose; Sebastian Stober; Oliver Speck; Andreas Nürnberger (CoRR, 2020)

Unboxing the Black-Box of Deep Learning Based Reconstruction of Undersampled MRIss. - Soumick Chatterjee; Arnab Das; Rupali Khatun; Andreas Nürnberger (XAI.it@AI*IA, 2023)

SMILE-UHURA Challenge - Small Vessel Segmentation at Mesoscopic Scale from Ultra-High Resolution 7T Magnetic Resonance Angiograms. - Soumick Chatterjee; Hendrik Mattern; Marc Dörner; Alessandro Sciarra; Florian Dubost; Hannes Schnurre; Rupali Khatun; Chun-Chih Yu; Tsung-Lin Hsieh; Yi-Shan Tsai; Yi-Zeng Fang; Yung-Ching Yang; et al. (CoRR, 2024)

Exploration of Interpretability Techniques for Deep COVID-19 Classification Using Chest X-ray Images. - Soumick Chatterjee; Fatima Saad; Chompunuch Sarasaen; Suhita Ghosh; Valerie Krug; Rupali Khatun; Rahul Mishra; Nirja Desai; Petia Radeva; Georg Rose; Sebastian Stober; Oliver Speck; et al. (J. Imaging, 2024)