S
Saurabh Shrivastava
Researcher at Bundelkhand University
Publications - 6
Citations - 66
Saurabh Shrivastava is an academic researcher from Bundelkhand University. The author has contributed to research in topics: Pattern recognition (psychology) & Pruning. The author has an hindex of 1, co-authored 3 publications receiving 46 citations.
Papers
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Journal ArticleDOI
Performance evaluation of feed-forward neural network with soft computing techniques for hand written English alphabets
TL;DR: It has been analyzed that the feed forward neural network by two Evolutionary algorithms makes better generalization accuracy in character recognition problems and can solve challenging problem most reliably and efficiently.
Journal ArticleDOI
Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A multicenter study using COVLIAS 2.0
Mohit Agarwal,Sushant Agarwal,Luca Saba,Gian Luca Chabert,Suneet K. Gupta,Alessandro Carriero,Alessio Paschè,Pietro Danna,Armin Mehmedović,Gavino Faa,Saurabh Shrivastava,Kanishka D Jain,Harsh Jain,Tanay Jujaray,Inder M. Singh,Monika Turk,Paramjit S. Chadha,Amer M. Johri,Narendra N. Khanna,Sophie Mavrogeni,John R. Laird,David W. Sobel,Martin Miner,Antonella Balestrieri,Petros P. Sfikakis,George Tsoulfas,Durga Prasanna Misra,Vikas Agarwal,George D. Kitas,Jagjit S Teji,Mustafa Al-Maini,Surinder Dhanjil,Andrew Nicolaides,Aditya Sharma,Vijay Rathore,Mostafa Fatemi,Azra Alizad,P. R. Krishnan,Rajanikant R Yadav,F. Nagy,Zsigmond Tamás Kincses,Zoltán Ruzsa,Subbaram Naidu,Klaudija Višković,Manudeep Kalra,Jasjit S. Suri +45 more
TL;DR: In this article , the authors proposed COVLIAS 2.0 using pruned AI (PAI) networks for improving both storage and speed, wiliest high performance on lung segmentation and lesion localization.
Proceedings ArticleDOI
Regularized CNN for Traffic Sign Recognition
TL;DR: Experimental results show that the proposed convolutional neural network outperforms the existing approaches for TSR and tries to train the system to respond in accordance with a rich dataset containing 39,209 color images spanned over 43 different categories of traffic signs.
Proceedings ArticleDOI
Comparative Analysis for Mining Fuzzified Dataset Using Association Rule Mining Approach
TL;DR: This paper has considered two types of dataset weather and forest fire information, both of which need to be fuzzifying and ARM is utilized to detect & study the relationship among regimes discovered in time series data from past years.
Proceedings ArticleDOI
Anomaly-based Intrusion Detection using GAN for Industrial Control Systems
TL;DR: In this paper , GAN based adversarial training is proposed to address the class imbalance problem in real-time datasets, where adversarial samples are combined with legitimate samples and shuffled via proper proportion and given as input to the classifiers.