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A Thorough Survey for Cricket Shot Analysis Using Deep Learning

Author(s):

Atharv Pushkraj Nirgude , MESCOE,PUNE; Rohit Dinesh Sonone, MESCOE,PUNE; Sahil Vikram Sonawane, MESCOE,PUNE; Rushikesh Sham Ahire, MESCOE,PUNE; Prof. Balaji Bodkhe, MESCOE,PUNE

Keywords:

Image Normalization, Convolutional Neural Networks

Abstract

there has been increased attention and popularity of various sports in the recent years. The lack of any sporting event in the midst of the recent pandemic had also left a large number of individuals craving to watch some sport being played. One of the majorly followed sport in India is easily cricket with millions of fans that follow the game religiously. The fans are very much into the game and perform in-depth analysis of the various players and their performances especially their shot selection. With the rise of the fantasy leagues and other similar applications, there is an increased interest in evaluation of the players that are performing better to help choose them in their teams. The manual process of batter shot identification is one of the most time consuming and highly laborious process which can benefit by some kind of automation. Therefore, this survey article analyzes the past works on cricket shot analysis which has been useful in determining our approach for the same using image processing implementations.

Other Details

Paper ID: IJSRDV10I20138
Published in: Volume : 10, Issue : 2
Publication Date: 01/05/2022
Page(s): 101-104

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