This model is a pretrained model on ILSVRC2012 dataset. This model is
able to achieve 54.5% Top-1 Accuracy and 78.3% Top-5 accuracy on
ILSVRC2012-Validation Set.
This model is a pretrained model on ILSVRC2012 dataset. This model is
able to achieve 58.8% Top-1 Accuracy and 81.3% Top-5 accuracy on
ILSVRC2012-Validation Set.
This model is a pretrained model on ILSVRC2012 dataset. This model is
able to achieve 55.4% Top-1 Accuracy and 78.8% Top-5 accuracy on
ILSVRC2012-Validation Set.
This model is a pretrained model on ILSVRC2012 dataset. This model is
able to achieve 71.0% Top-1 Accuracy and 89.8% Top-5 accuracy on
ILSVRC2012-Validation Set.
This model is a pretrained model on ILSVRC2012 dataset. This model is
able to achieve 71.0% Top-1 Accuracy and 89.8% Top-5 accuracy on
ILSVRC2012-Validation Set.
This model is a pretrained model on ILSVRC2012 dataset. This model is
able to achieve 72.5% Top-1 Accuracy and 90.8% Top-5 accuracy on
ILSVRC2012-Validation Set.
This model is converted from TensorFlow released pretrained model. By
single crop on 299 x 299 image from 384 x 384 image, this model is able
to achieve 76.88% Top-1 Accuracy and 93.344% Top-5 Accuracy on
ILSVRC2012-Validation Set.
This model is a pretrained model on full imagenet dataset with
14,197,087 images in 21,841 classes. The model is trained by only random
crop and mirror augmentation. This model is able to achieve 37.19%
Top-1 accuracy on training data. This model is about 50% more complex
than standard Inception-BN Network