Enhanced Yolov5 Based Approach for Effective Agricultural Pest Detection

Agricultural pest detection is a major challenge for farmers globally, affecting both crop health and productivity. Many current detection systems suffer from low accuracy and high false alarm rates, resulting in significant crop damage and financial losses. To address the persistent threat pests, pose to agricultural sustainability, innovative detection methods are crucial for minimizing risks and ensuring food security. The proposed system offers several improvements over existing methods, including enhanced accuracy in pest detection, fewer false alarms, and the capability to identify specific pest species and their damage. Furthermore, the use of Enhanced YOLOv5 for automated pest detection promises to increase efficiency and cost-effectiveness in managing agricultural pests.