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Journal of Big Data

Table 2 The summary Of VGG16 layered architecture. Architecture

From: Review of deep learning methods for remote sensing satellite images classification: experimental survey and comparative analysis

Block

Units (n)

Operators (F)

Resolutions (\({H} \times {W}\))

Channels (C)

Block A

2

Conv, ReLu, MaxPool

\(224\times 224\)

64

Block B

112

Conv, ReLu, BatchNorm

\(112\times 112\)

128

Block C

1

Conv, ReLu, BatchNorm, AvgPool

56 \(\times\) 56

256

Block D

1

Conv, ReLu, BatchNorm, AvgPool

56 \(\times\) 56

256

Block E

1

Conv, ReLu, AvgPool, AdaptiveAvgPool, AdaptiveMaxpool

28 \(\times\) 28

512

Block F

1

Linear, Relu, BatchNorm

28 \(\times\) 28

512

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