Table 7 Parameters, FLOPs, and MACs of each model used in the research.

From: PolSAR image classification using shallow to deep feature fusion network with complex valued attention

Model

Parameters

FLOPs

MACs

ResNet

27,790,223

8,403,968

4,201,984

VGG19

20,294,735

539,648

269,824

2D-CVNN

28,794

383,568

191,484

WaveletCNN

4,714,043

195,928,265

97,964,133

CV-CNN-SE

1,528,546

3,843,424

1,904,288

3D-CVNN

1,871,422

1,774,176

886,656

ASDF2Net

5,241,002

5,242,600

2,611,136

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