Image Classification on Plnk (test)
74.5Top-1 AccVGG-B(S)
Evaluation Results
| Method | Links | |
|---|---|---|
| VGG-B(S)Backbone=VGG-B, Pre-training=trained from scratch, #par=82017.05 | 74.5 | |
| VGG-B(P)Backbone=VGG-B, Pre-training=pre-trained on ImageNet, #par=82017.05 | 73.2 | |
| DAN_imagenetBackbone=VGG-B, Controller Initialization=ImageNet, #par=2.762017.05 | 72.5 | |
| DAN_imagenet+sketchBackbone=VGG-B, Controller Initialization=ImageNet + Sketch, #par=3.322017.05 | 72.5 | |
| DAN_sketchBackbone=VGG-B, Controller Initialization=sketch, #par=2.542017.05 | 69.6 | |
| DAN_caltech-256Backbone=VGG-B, Controller Initialization=caltech-256, #par=2.542017.05 | 63.6 | |
| DAN_noiseBackbone=VGG-B, Controller Initialization=random weights, #par=1.762017.05 | 61.7 |