AI RESEARCH
Small Object Detection in Industrial Recycling: A New Dataset and YOLO Performance Evaluation
arXiv CS.CV
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ArXi:2605.26884v1 Announce Type: new In this paper, we address the problem of detecting small, dense, and overlapping objects, a major challenge in computer vision. Our focus is on reviewing proposed methods based on deep learning supervised approaches. We provide a detailed comparison of these systems on a new dataset of than 10k images and 120k instances, highlighting their performance, accuracy, and computational efficiency in the industrial recycling process use case.