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Varad Pimpalkhute

Varad Pimpalkhute
Indian Institute of Information Technology, Nagpur · Electronics and Communication Engineering

Bachelor of Technology

About

7
Publications
797
Reads
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35
Citations
Introduction
I am currently interested in working in Deep Learning and Algorithm Optimisation. I want to particularly focus on building systems which surpass human performance.
Additional affiliations
May 2019 - July 2019
Indian Institute of Technology Gandhinagar
Position
  • Summer Research Intern
December 2018 - January 2019
Indian Institute of Technology Gandhinagar
Position
  • Winter Research Intern
Education
July 2017 - May 2021
Indian Institute of Information Technology Nagpur (IIITN)
Field of study
  • Electronics and Communication Engineering

Publications

Publications (7)
Article
Full-text available
Sleep is one of the most important body mechanisms responsible for the proper functioning of human body. Cyclic alternating patterns (CAP) play an indispensable role in the analysis of sleep quality and related disorders like nocturnal front lobe epilepsy, insomnia, narcolepsy etc. The traditional manual segregation methods of CAP phases by the med...
Article
Noise type and strength estimation are important in many image processing applications like denoising, compression, video tracking, etc. There are many existing methods for estimation of the type of noise and its strength in digital images. These methods mostly rely on the transform or spatial domain information of images. We propose a hybrid Discr...
Preprint
Full-text available
Meta Learning has been in focus in recent years due to the meta-learner model's ability to adapt well and generalize to new tasks, thus, reducing both the time and data requirements for learning. However, a major drawback of meta learner is that, to reach to a state from where learning new tasks becomes feasible with less data, it requires a large...
Preprint
Full-text available
Much of the recent research work in image retrieval, has been focused around using Neural Networks as the core component. Many of the papers in other domain have shown that training multiple models, and then combining their outcomes, provide good results. This is since, a single Neural Network model, may not extract sufficient information from the...

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