A Comparative Analysis of Machine Vision Algorithms for Insect Pests Classification - Nitin; Gupta, Satinder Bal (Journal of Artificial Intelligence and Capsule Networks, 2022)
Insect pests are the one of the important biological factors, that has become an important cause of crop yield degradation. However, their identification and detection in the early stages is a very significant task to minimize the overall losses. The conventional techniques with naked eyes to identify the pests is very exigent and require domain specific expertise. It is extremely time-consuming and tedious task to identify the pests in the initial stages with conventional methods. To minimize these issues, some highly developed methods are required to detect insect pests accurately in agriculture. The continuous emergence of machine vision in image processing helps in this regard. This paper presents a comprehensive review to identify the insect pests in the early stages with the help of machine vision techniques. Based on this, a comparative analysis of different classifiers has also been presented.
Keywords: Artificial intelligence; smart agriculture; classification; pest detection