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Post by account_disabled on Feb 18, 2024 4:09:37 GMT
In this case, the gradients of the trained parameters are calculated in each layer, and at the end of backpropagation the weights are updated using gradient descent. Structure of a convolutional neural network By their structure, convolutional neural networks are like a funnel: everything starts with the big picture, then attention switches to individual details. The brain works in exactly the same way: a person on the street first sees a cat and only then begins to consider the color of its fur and eyes. This is called representational learning. Structure of a Phone Number List convolutional neural network Structure of a convolutional neural network A convolutional neural network consists of several layers. of training depend on the number of layers. Here is a diagram of the main components of a convolutional neural network: convolutional layer; pooling; normalization by batch; fully connected layer. The best free and shareware neural networks Read also The best free and shareware neural networks More details In order for a neural network to recognize a cat, it is necessary to perform several typical operations on each image layer. The key to these operations is convolution. A gift for you! Freely available until 18.02 Download the TOP 10 neural networks that will help make your work easier To receive the file, enter your email: E-mail, for example, ru Confirm that you are not a robot by entering your phone number: Download the selection for free I confirm my consent to the processing of personal data During the convolution process, the neural network removes the unnecessary and leaves the useful, i.
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