Dishant Padalia
Dishant Rohit Padalia is a B.Tech. in Electronics and Telecommunications Engineering student from K.J. Somaiya College of Engineering, Vidyavihar. His interests include Deep Learning, Computer Vision and Natural Language Processing. He has worked as a Research Intern under my mentorship. As a research intern, Dishant worked on a project to develop a deep learning-based solution for detecting Alzheimer's Disease using Positron Emission Tomography (PET) scan images of the brain. He also authored a research paper titled ‘DeepPET-3D: A Deep Learning Based 3D-CNN Model for Diagnosis of Alzheimer's Disease Using 18-FDG-PET.’
Dishant has worked on several other research projects. He has great technical acumen and great problem solving skills. His approach to remove the pectoral muscle from the mammography images aided in increasing the classification accuracy from 83.23% to 97.14%. Moreover, he has authored a technical paper titled ‘EEF-Net: An Enhanced EfficientNet for Breast Tumor Classification in Mammograms’ based on the work done in this project, which is currently under review in ‘Clinical Breast Cancer’ journal. His paper, ‘MRI image denoising using U-Net and Image Processing Techniques’ has been accepted for publication in the 5th IEEE International Conference on Advances in Science and Technology 2022.
Currently, he is working as a Machine Learning Research Intern at IIT Bombay CSE department, where he has developed Layout analysis, detection and recognition models for the OCR and digitization of documents in Indian languages.
Portfolio Website – dishantpadalia.me
LinkedIn - http://linkedin.com/in/dishant-padalia/
Google Scholar - https://scholar.google.com/citations?user=M5bIR70AAAAJ
GitHub - http://github.com/dishant26
LoR from Dr. Ninad
Dishant has worked on several other research projects. He has great technical acumen and great problem solving skills. His approach to remove the pectoral muscle from the mammography images aided in increasing the classification accuracy from 83.23% to 97.14%. Moreover, he has authored a technical paper titled ‘EEF-Net: An Enhanced EfficientNet for Breast Tumor Classification in Mammograms’ based on the work done in this project, which is currently under review in ‘Clinical Breast Cancer’ journal. His paper, ‘MRI image denoising using U-Net and Image Processing Techniques’ has been accepted for publication in the 5th IEEE International Conference on Advances in Science and Technology 2022.
Currently, he is working as a Machine Learning Research Intern at IIT Bombay CSE department, where he has developed Layout analysis, detection and recognition models for the OCR and digitization of documents in Indian languages.
Portfolio Website – dishantpadalia.me
LinkedIn - http://linkedin.com/in/dishant-padalia/
Google Scholar - https://scholar.google.com/citations?user=M5bIR70AAAAJ
GitHub - http://github.com/dishant26
LoR from Dr. Ninad