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Models/YOLOv5x

YOLOv5x

Reported on 10 benchmarks across 5 tasks · 2 papers

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology8 results

  • 3DonGRAZPEDWRI-DX
    mAP· uses extra data· 2024-07-17
    69
    best: 77 (YOLOv8x)
    Enhancing Wrist Fracture Detection with YOLOarXiv:2407.12597
  • 2D ClassificationonGRAZPEDWRI-DX
    mAP· uses extra data· 2024-07-17
    69
    best: 77 (YOLOv8x)
    Enhancing Wrist Fracture Detection with YOLOarXiv:2407.12597
  • 2D Object DetectiononGRAZPEDWRI-DX
    mAP· uses extra data· 2024-07-17
    69
    best: 77 (YOLOv8x)
    Enhancing Wrist Fracture Detection with YOLOarXiv:2407.12597
  • 16konGRAZPEDWRI-DX
    mAP· uses extra data· 2024-07-17
    69
    best: 77 (YOLOv8x)
    Enhancing Wrist Fracture Detection with YOLOarXiv:2407.12597
  • 3DonIndia Driving Dataset
    mAP@0.5· 2023-04-14
    30.3
    best: 81.1
    YOLO-Drone:Airborne real-time detection of dense small objects from high-altitude perspectivearXiv:2304.06925
  • 2D ClassificationonIndia Driving Dataset
    mAP@0.5· 2023-04-14
    30.3
    best: 81.1
    YOLO-Drone:Airborne real-time detection of dense small objects from high-altitude perspectivearXiv:2304.06925
  • 2D Object DetectiononIndia Driving Dataset
    mAP@0.5· 2023-04-14
    30.3
    best: 81.1
    YOLO-Drone:Airborne real-time detection of dense small objects from high-altitude perspectivearXiv:2304.06925
  • 16konIndia Driving Dataset
    mAP@0.5· 2023-04-14
    30.3
    best: 81.1
    YOLO-Drone:Airborne real-time detection of dense small objects from high-altitude perspectivearXiv:2304.06925

Computer Vision2 results

  • Object DetectiononGRAZPEDWRI-DX
    mAP· uses extra data· 2024-07-17
    69
    best: 77 (YOLOv8x)
    Enhancing Wrist Fracture Detection with YOLOarXiv:2407.12597
  • Object DetectiononIndia Driving Dataset
    mAP@0.5· 2023-04-14
    30.3
    best: 81.1
    YOLO-Drone:Airborne real-time detection of dense small objects from high-altitude perspectivearXiv:2304.06925