Harshit Tiwari
Memorial University of Newfoundland
6 Papers
Harshit Tiwari is an academic researcher from Memorial University of Newfoundland. The author has contributed to research in topics: Noise & Computer science. The author has an hindex of 4, co-authored 4 publications.
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Papers
A Non-Local Means Filtering Algorithm for Restoration of Rician Distributed MRI
Vikrant Bhateja,Harshit Tiwari,Aditya Srivastava +2 more
- 01 Jan 2015
TL;DR: This paper presents a Non-Local Means (NLM) based filtering algorithm for denoising Rician distributed MRI that utilizes the concept of self-similarity which considers the weighted average of all the pixels by identifying the similar and dissimilar windows based on Euclidean distance for MRI restoration.
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Restoration Algorithm for Gaussian Corrupted MRI Using Non-local Averaging
Aditya Srivastava,Vikrant Bhateja,Harshit Tiwari,Suresh Chandra Satapathy +3 more
- 01 Jan 2015
TL;DR: A Non-Local Averaging based MRI denoising algorithm to facilitate preservation of the finer structures by computes the weighted average of the similar pixels of the image within the local window.
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•Proceedings Article
Modified Anisotropic Diffusion filtering algorithm for MRI
Aditya Srivastava,Vikrant Bhateja,Harshit Tiwari +2 more
- 11 Mar 2015
TL;DR: The proposed modified Anisotropic Diffusion algorithm aimed to improve the estimation of the diffusion constant to facilitate better edge detection and preservation of details has shown stable value of evaluation parameters at higher noise variances.
11
Exploring Deep Learning Models Aimed at Favorable Optimization and Enhancement of Fiber Optic Sensor’s Performance
Harshit Tiwari,Yogendra S. Dwivedi,Rishav Singh,Baljinder Kaur,Yogendra Kumar Prajapati,Richa Krishna,Nitin Singh Singha,Anuj Kumar Sharma +7 more
TL;DR: This study proposes a deep learning-assisted approach to optimize fiber optic sensor performance using a recurrent neural network, achieving promising results with a root-mean-square error of 2.12 and processing time significantly faster than traditional simulation techniques.
8
•Proceedings Article
Estimation based non-local approach for pre-processing of MRI
Harshit Tiwari,Vikrant Bhateja,Aditya Srivastava +2 more
- 11 Mar 2015
TL;DR: A patch based approach where the decomposed patches of MRI with low texture strength are selected on the basis of gradient covariance matrix are used to estimate the noise level through Principal Component Analysis (PCA) to improve the noise suppression.
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