Author:
Nitin ,Satinder Bal Gupta
Abstract
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.
Publisher
Inventive Research Organization
Reference25 articles.
1. [1] Nagaraja, G. S., Soppimath, A. B., Soumya, T., & Abhinith, A. (2019). IoT Based Smart Agriculture Management System. 4th International Conference On Computational Systems And Information Technology For Sustainable Solution (CSITSS).
2. [2] Guguloth Chanti, (2017). Agriculture Policy In India -A Study Of The Living Conditions Of Rural Villager’s Due To The Green Revolution. International Journal Of Scientific Research And Management (IJSRM) vol- 5, I-08, pp 6863-6868.
3. [3] Shakunthala Sridhara, (2006). An Overview Of Vertebrate Pests In India. Published At Univ. Of Calif., Davis. 22(22)
4. [4] Mohd Javaid, Abid Haleem, Ibrahim Haleem Khan, Rajiv Suman,.(2022). Understanding the potential applications of Artificial Intelligence in Agriculture Sector, Advanced Agrochem.
5. [5] A. M. K. Siu And R. W. H. Lau(2005). "Image Registration For Image-Based Rendering," In IEEE Transactions On Image Processing, Vol. 14, No. 2, pp. 241-252.