A Lightweight Garbage Classification Algorithm Based on The Improved YOLOv10s

Abstract

Garbage classification is an important task for environmental protection and resource recycling. This paper proposes a lightweight garbage classification algorithm based on the improved YOLOv10s model. By introducing structural improvements to reduce computational complexity while maintaining classification accuracy, the proposed method achieves efficient real-time garbage detection and classification suitable for deployment on edge devices.