Table 2 Layers property of the CNN architecture. The network consists of twenty-five layers. There are eight layers with learnable weights: five convolutional layers, and three fully connected layers
No. | Layer name | Description |
|---|---|---|
1 | Image input | 227 × 227 × 3 true color images with zerocenter standardization |
2 | 1st-level convolution | 96 channels, 11 × 11 × 3 convolutions |
3 | ReLU | Rectified linear units |
4 | Cross channel standardization | Cross channel standardization with 5 channels per element |
5 | Max pooling | 3 × 3 max pooling |
6 | 2nd-level convolution | 256 channels, 5 × 5 × 48 convolutions |
7 | ReLU | Rectified linear units |
8 | Cross channel standardization | Cross channel standardization with 5 channels per element |
9 | Max pooling | 3 × 3 max pooling |
10 | 3rd-level convolution | 384 channels, 3 × 3 × 256 convolutions |
11 | ReLU | Rectified linear units |
12 | 4th-level convolution | 384 channels, 3 × 3 × 192 convolutions |
13 | ReLU | Rectified linear units |
14 | 5th-level convolution | 256 channels, 3 × 3 × 192 convolutions |
15 | ReLU | Rectified linear units |
16 | Max pooling | 3 × 3 max pooling |
17 | 6th-level fully connected layer | 4096 fully connected layer |
18 | ReLU | Rectified linear units |
19 | Dropout | 50% of dropout |
20 | 7th-level fully connected layer | 4096 fully connected layer |
21 | ReLU | Rectified linear units |
22 | Dropout | 50% of dropout |
23 | 8th-level fully connected layer | 4 fully connected layer |
24 | Softmax | Softmax |
25 | Comprehension output | Crossentropyex with Androsace umbellata (Lour.) Merr., Bidens pilosa L., Trifolium repens L. and Fragaria × ananassa |