In deep learning, if an image is entered with RGB values, the feature extraction related to color information will only be performed in the first layer.However, color images can be generated from black and white images.If you have any knowledge of this point, I would appreciate it if you could let me know.
python deep-learning
The deep learning model only looks at the numbers entered and performs the sum-of-product sum operations
When expanding black and white (channel 1) to RGB (channel 3), we try to figure out which channel and where and how many numbers should be placed to reduce the difference between the correct answer and the correct answer.Therefore, in which layer and what feature quantities are extracted is a black box.
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