IDENTIFICATION OF COLORADO BEETLES USING YOLOV5

Abstract

The monitoring of Colorado potato beetles in large fields is a complex and time-consuming process that requires accurate data collection, analysis, and interpretation. The use of artificial intelligence (AI) can greatly simplify this complex process by automatically monitoring fields and detecting beetles marking locations of their location. We trained an object detection neural network using YOLOv5 framework using the dataset with 150 images of the Colorado potato beetles photographed in the natural conditions. We trained YOLOv5s model and got the most perfect result that was 0.995 mAP. Using the best trained neural network, we can now put videos and image files in the code and the neural network will run and detect all the Colorado potato beetles in the given files automatically.