A Dense U-Net Architecture for Multiple Sclerosis Lesion Segmentation. - Amish Kumar; Oduri Narayana Murthy; Shrish; Palash Ghosal; Amritendu Mukherjee; Debashis Nandi (TENCON, 2019)

CSNet: A new DeepNet framework for ischemic stroke lesion segmentation. - Amish Kumar; Neha Upadhyay; Palash Ghosal; Tamal Chowdhury; Dipayan Das 004; Amritendu Mukherjee; Debashis Nandi (Comput. Methods Programs Biomed., 2020)

Development of New Index-Based Methodology for Extraction of Built-Up Area From Landsat7 Imagery: Comparison of Performance With SVM, ANN, and Existing Indices. - Amritendu Mukherjee; Arjun Anil Kumar; Parthasarathy Ramachandran (IEEE Trans. Geosci. Remote. Sens., 2021)

Filtering Super-Resolution Scan Conversion of Medical Ultrasound Frames. - Dipannita Ghosh; Amish Kumar; Palash Ghosal; Amritendu Mukherjee; Debashis Nandi (Wirel. Pers. Commun., 2021)

Development of New Index Based Supervised Algorithm for Separation of Built-Up and River Sand Pixels from Landsat7 Imagery: Comparison of Performance with SVM. - Amritendu Mukherjee; Parthasarathy Ramachandran (IGARSS, 2022)

A lightweight asymmetric U-Net framework for acute ischemic stroke lesion segmentation in CT and CTP images. - Amish Kumar; Palash Ghosal; Soumya Snigdha Kundu; Amritendu Mukherjee; Debashis Nandi (Comput. Methods Programs Biomed., 2022)

Application of Generative Adversarial Network (GAN) for Synthetic Training Data Creation to improve performance of ANN Classifier for extracting Built-Up pixels from Landsat Satellite Imagery. - Amritendu Mukherjee; Dipanwita Sinha Mukherjee; Parthasarathy Ramachandran (CoRR, 2025)