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Lal Chand
Punjabi University Patiala

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A multi-instance learning based approach for whitefly pest detection Lal Chand; Amardeep Singh Dhiman; Sikander Singh
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 2: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i2.pp1050-1060

Abstract

Agriculture constantly faces various challenges including attacks from new pests and insects. With large farm sizes and plummeting manpower in the agricultural sector, it becomes challenging to continuously monitor crops for pest infestation. In this research paper, a specific type of pest attack known as the white fly attack has been investigated which affects a variety of crops. This paper presents four different approaches for automated classification of whiteflies which are the Bayesian network, convolution neural network (CNN), ResNet and multi-instance learning-CNN. A comparative analysis with conventional machine learning and deep learning techniques has also been presented. The performance of the proposed technique has been evaluated in terms of the classification accuracy. The experimental results obtained show that the proposed technique attains a classification accuracy of 95.53%, 96.9%, 97.6% and 98.13% for the four models respectively. A comparative analysis in terms of accuracy of classificaiton, with existing techniques shows that the proposed technique outperforms baseline deep learning models identifying whitefly infestation.
Co-Authors Amardeep Singh Dhiman Sikander Singh