Table 3.

Learning parameters used for training and fine-tuning of AlexNet for AFT in our experiments. μ is the momentum, lr_fc8 is the learning rate of the weights in the last layer, α is the learning rate of the weights in the rest layers, and γ determines how lr decreases over epochs. “Epochs” indicates the number of epochs used in each step. For ACFT, all the parameters are set to the same as AFT except the learning rate lr, which is set to 1/10 of that for AFT.

Applications	μ	lr	lr fc8	γ	epoch
Colonoscopy frame classification	0.9	1e-4	1e-3	0.95	8
Polyp detection	0.9	1e-4	1e-3	0.95	10
Pulmonary embolism detection	0.9	1e-3	1e-2	0.95	5