Table 1 Output shape and number of parameters for Spatial-autoencoder and FFT-autoencoders for HAM10000 and ISIC-2017 dataset.

From: Skin cancer detection through attention guided dual autoencoder approach with extreme learning machine

 

Layer name

Output shape (HAM10000)

Output shape (ISIC-2017)

#Params

Encoder

Input

[28,28,3]

[64,64,3]

0

Conv1

[28,28,32]

[64,64,32]

896

Channel_attention1

[28,28,32]

[64,64,32]

256

Maxpool1

[14,14,32]

[32,32,32]

0

Conv2

[14,14,16]

[32,32,16]

4624

Channel_attention1

[14,14,16]

[32,32,16]

64

Maxpool2

[7,7,16]

[16,16,16]

0

Decoder

Conv3

[7,7,16]

[16,16,16]

2320

UpSample1

[14,14,16]

[32,32,16]

0

Conv4

[14,14,32]

[32,32,32]

4640

UpSample2

[28,28,32]

[64,42,32]

0

Conv5

[28,28,3]

[64,64,3]

867

Total parameters

  

13,667