@inproceedings{d6e78dcfecd54222b8d7f2d5c35d76f6,
title = "Intelligent classification model for Indian chickpea",
abstract = "India is one of the major chickpea-producing countries in the world. An estimate of almost 71 % of the world's chickpea production is done here. This paper presents an approach to classify Indian chickpeas using a computer vision technique. For this work image processing and eight different machine learning algorithms are used. The features considered are first of their kind. Based on these features the performance of machine learning algorithms is studied for the classification of the chickpea. Out of eight different algorithms lib Support Vector Machine and multilinear perceptron provided high accuracy of 86.07% and 84.90%. ",
author = "Kini, {Anita S.} and Prema, {K. V.} and Pai, {Smitha N.}",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 5th International Conference on Intelligent Computing and Control Systems, ICICCS 2021 ; Conference date: 06-05-2021 Through 08-05-2021",
year = "2021",
month = may,
day = "6",
doi = "10.1109/ICICCS51141.2021.9432129",
language = "English",
series = "Proceedings - 5th International Conference on Intelligent Computing and Control Systems, ICICCS 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1847--1852",
booktitle = "Proceedings - 5th International Conference on Intelligent Computing and Control Systems, ICICCS 2021",
address = "United States",
}