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IEEE/ICACT20210175 Slide.21        [Big Slide]	Oral Presentation
	Here is an illustration of a typical CNN architecture showing how they are connected from input to output. It consists of three types of heterogeneous layers: convolutional layers, pooling layers, and fully connected layers. The first part consists of Convolutional and max-pooling layers which act as the feature extractor. The second part consists of the fully connected layer which performs non-linear transformations of the extracted features and acts as the classifier.

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