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![[Figure 4]](gm5087fig4mag.jpg)
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Figure 4
(a) General operation of a convolutional layer to create a feature map. Colours and grey shades refer to example numbers written in the fields. A patch (the local receptive field) of the input array is altered through multiple filters and the resulting values are saved in the feature map. (b) Like a convolutional layer, the pooling layer is only connected to a limited group of inputs within a rectangular field. However, it has no filter and only summarizes the input matrix through aggregation. (c) The flatten layer flattens the multidimensional matrix into a single-dimensional matrix; the output is passed to a regular neural network made of fully connected artificial neurons. |
![[Figure 4]](gm5087fig4.jpg)
 | STRUCTURAL BIOLOGY |
ISSN: 2059-7983
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