An improved YOLOv8-based pest detection model for detecting elongate larvae

Agriculture, an integral part of human existence, plays a central role in the economic and strategic sphere of every country. Crop productivity is of concern to all, as pests and diseases can significantly reduce yields or even lead to the death of crops. Therefore, the detection of such threats is of utmost importance. With the advances in deep learning, the application of object detection algorithms to identify and monitor these problems has gained momentum. The present work uses the improved YOLOv8 algorithm as a foundation and introduces extensions that show improved performance on the widely recognized IP102 dataset intended for public insect images.