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In this article, the concept of ensemble learning and its usage in deep learning for super resolution is discussed with the help of one of its applications in the paper ‘MRI Super-Resolution with Ensemble Learning and Complementary Priors’ as an example.
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This is the second part of the Super resolution series. It’s mainly about supervised superresolution and an introdution to frameworks used in this domain.
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This article is mainly aimed at Machine Learning and Computer Vision enthusiasts with little or no background in these fields. In this part, I briefly introduced the concept of Super-Resolution and its confounding applications in various fields. I also discussed a few initial algorithms which paved the way to current progress in this domain.
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In this article, the highlights of EnhanceNet paper for single image super-resolution and the performance of various versions of it are discussed. I would like to mainly emphasize its loss functions which are responsible for a perceptual quality close to the original high-resolution image.
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Published in International Conference on Mobile Computing and Sustainable Informatics (ICMCSI), 2020
This paper is about a Web application using MERN stack to enhance classroom interaction via real-time feedback and queries
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Published in Under review at the IEEE Transactions on Image Processing, 2020
This paper is about a novel Generative Adversarial Network based model to super resolve digital rock images
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This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
Undergraduate course, Computer Science Department, BITS Pilani - India, 2017
Course: Computer Programming Teaching Assistant to Professor Barsha Mitra for the course CS F111 Computer Programming (Lecture, Practical).
Undergraduate courses, Economics Department, BITS Pilani - India, 2018
Courses:
Undergraduate Thesis, Computational Data Science Department, Indian Institute of Science, 2019
Research Intern in the Medical Image Processing (MIG) lab headed by Prof.Phaneendra Yalavarthy of the Computational Data Science department at IISc, Bangalore.
Graduate Research, Computational Data Science Department, Indian Institute of Science, 2020
Research Assistant in the Medical Image Processing (MIG) lab headed by Prof.Phaneendra Yalavarthy of the Computational Data Science department at IISc, Bangalore. My research was in collaboration with the Royal Dutch Shell Technology Centre, Bangalore - India
Graduate Research, World Well-Being Project, University of Pennsylvania, 2021
Research Assistant to Dr. Lyle Ungar, Professor in Computer and Information Science at Penn Engineering and Psychology at the School of Arts & Sciences, and, Dr. Sharath Chandra Guntuku, an Assistant Professor (Research) in the Department of Computer and Information Science at the University of Pennsylvania.