Hyperspectral Image Classification Model Using Squeeze and Excitation Network with Deep Learning

Table 1

Parameters of CNN model.

Layer	Parameters
Input	Input image with a size of (64 × 64, 3)
C1	Conv 2D (32, 3 × 3)
BN1	Batch normalization
P1	Maxpooling 2D (2, 2)
C2	Conv 2D (32, 3 × 3)
P2	Maxpooling 2D (2, 2)
C3	Conv 2D (64, 3 × 3) drop out (0.35) ReLU
P3	Maxpooling 2D (2, 2)
C4	Conv 2D (128, 3 × 3)
P4	Maxpooling 2D (2, 2)
FC1	1024
FC2	256
Output	Classification of images