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Fig. 4 | BioMedical Engineering OnLine

Fig. 4

From: Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network

Fig. 4

Visualization of first-layer convolution kernels and feature maps for the CS-ResCNN method. The green and red squares denote the captured edges and color characteristics, respectively. a Original retro-illumination image. b The 64 convolution kernels with dimensions of 7 × 7 projected into pixel space. c The 64 feature maps with dimensions of 56 × 56

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