Object Detection on Poplar-Leaf (test)
65.8mAPLeafInst
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| LeafInstBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 65.8 | 90.4 | 71 | |
| YOLOV8Backbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 65.7 | 90.5 | — | |
| YOLOV11Backbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 64.9 | 90.4 | — | |
| CascadeRcnnBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 62.4 | 83 | 69.8 | |
| PointRendBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 61.7 | 84.6 | 68.2 | |
| MaskRcnnBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 61.2 | 89.8 | 65.2 | |
| BoxInstBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 61.2 | 88.1 | 66.4 | |
| MaskDinoBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 57.8 | 81.1 | 60.1 | |
| QueryinstBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 55.7 | 79.2 | 59.5 | |
| Mask2formerBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 55.1 | 75.6 | 58 | |
| YOLACTBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 45.7 | 79.2 | 47.7 |