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Figure 2 – uploaded by Avijit Chaudhuri
Figure 2 of a rectangular neighbourhood is taken and used as the representative value for that neighbourhood. This helps to reduce the spatial dimensionality of the data and extract the most important features while preserving the most prominent patterns. In the cur- rent model, MaxPooling is being used with a win- dow size of 2x2 and 2x2 strides to further reduce the size of the features extracted by the convolutional layer. connected layers are some examples of the layers that may be used while building a CNN. Moreover, each layer’s characteristics, including the quantity and size of filters, must be supplied. The general architecture of the CNN is built using these layers and parameters, which affects how well it completes the task at hand.
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