Large Scale Image Classification With Deep Convolutional Feature Learning

via “multi-scale feature pyramid detection across image resolutions”

object-detection model by undefined. 1,29,977 downloads.

Unique: YOLOv10 uses an improved PAN (Path Aggregation Network) with bidirectional feature fusion, enabling better information flow between scales compared to YOLOv8's simpler FPN, resulting in ~2-3% mAP improvement on small objects.

vs others: More efficient than Faster R-CNN's region proposal approach for multi-scale detection; simpler than cascade detectors (which require multiple stages) while achieving comparable accuracy on small objects.