Object Detection on MONKEY Challenge 1.0 (test)
39.3Inflammatory Cells FROCKongNet (Wide)
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| KongNet (Wide)Architecture=Wide2025.10 | 39.3 | 46.24 | 23.92 | |
| Team InstanSegMethodology=InstanSeg + Classifier2025.10 | 38.75 | 45.15 | 26.26 | |
| Team AIRA MatrixMethodology=DETR and YOLOv5-L2025.10 | 35.17 | 44.71 | 19.06 | |
| Team ST MedicalMethodology=YOLOv11 + Classifier2025.10 | 33.16 | 39.35 | 12.68 | |
| Team BioTotemMethodology=Customised CNN2025.10 | 31.3 | 37.02 | 12.3 | |
| Team ouradiologyMethodology=Two Faster R-CNN models2025.10 | 28.24 | 37.03 | 15.5 | |
| Team Zip Lab UNIMOREMethodology=CellViT2025.10 | 24.7 | 30.49 | 6.99 | |
| BaselineMethodology=Faster R-CNN trained by organisers2025.10 | 22.82 | 31.2 | 12.2 |