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. 2020 Oct 7;8(10):E1448–E1454. doi: 10.1055/a-1229-3927

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The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commecial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.

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Fig. 3 — Architecture of the underlying convolutional neural network (“AlexNet”) with an exemplary image showing the activation of three convolutional layers. As raw image data passes through the CNN model, higher-level features of the polyp (bottom of the image) begin to emerge.