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Analytical Review of Major Nocturnal Pests’ Detection Technique using Computer Vision


Affiliations
1 Information Technology Cell, Junagadh Agricultural University, Junagadh, Gujarat, India
2 Department of Computer Engineering, RK University, Kasturbadham, Rajkot, Gujarat, India
 

1* and Nirav rav Bhattatt 2Research in agriculture is increasing quality and quantity, but pest reduces it. To prevent the effect of these pests, insecticides are used. But excessive use of pesticides is very harmful to production and environment. So initially pest detection is necessary. We work on nocturnal pests because that can be easily attracting using night trapping tools. The purpose of this review article is to analyse the popular techniques and find the right technique for the initial diagnosis and early detection of major nocturnal flying pests like Pink Bollworm, White Grub, Helicoverpa and Spodoptera. The importance of early detection can be in identifying and classifying the pests in a digital view. We have concluded our results with the various methods and the prospects of future research.

Keywords

Computer Vision, Pest Detection Techniques, Convolution Neural Networks, Deep Learning.
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  • Analytical Review of Major Nocturnal Pests’ Detection Technique using Computer Vision

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Authors

Deven J. Patatel
Information Technology Cell, Junagadh Agricultural University, Junagadh, Gujarat, India
Nirav Bhattatt
Department of Computer Engineering, RK University, Kasturbadham, Rajkot, Gujarat, India

Abstract


1* and Nirav rav Bhattatt 2Research in agriculture is increasing quality and quantity, but pest reduces it. To prevent the effect of these pests, insecticides are used. But excessive use of pesticides is very harmful to production and environment. So initially pest detection is necessary. We work on nocturnal pests because that can be easily attracting using night trapping tools. The purpose of this review article is to analyse the popular techniques and find the right technique for the initial diagnosis and early detection of major nocturnal flying pests like Pink Bollworm, White Grub, Helicoverpa and Spodoptera. The importance of early detection can be in identifying and classifying the pests in a digital view. We have concluded our results with the various methods and the prospects of future research.

Keywords


Computer Vision, Pest Detection Techniques, Convolution Neural Networks, Deep Learning.

References