English: Figure 6 from Andreas Maier, Christopher Syben. Tobias Lasser. Christian Riess. "A gentle introduction to deep learning in medical image processing". Zeitschrift für Medizinische Physik
Please reference this article, if you reuse this figure.
Original Caption: Convolutional layers only face a limited preceptive field and all neurons share the same weights (cf. left side of the figure; adopted from [40]). Pooling layers reduce the total input size. Both are typically combined in an alternating manner to construct convolutional neural networks (CNNs). An example is shown on the right.
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Convolutional layers only face a limited preceptive field and all neurons share the same weights (cf. left side of the figure). Pooling layers reduce the total input size.
English: Figure 6 from Andreas Maier, Christopher Syben. Tobias Lasser. Christian Riess. "A gentle introduction to deep learning in medical image processing". Zeitschrift für Medizinische Physik
Please reference this article, if you reuse this figure.
Original Caption: Convolutional layers only face a limited preceptive field and all neurons share the same weights (cf. left side of the figure; adopted from [40]). Pooling layers reduce the total input size. Both are typically combined in an alternating manner to construct convolutional neural networks (CNNs). An example is shown on the right.
to share – to copy, distribute and transmit the work
to remix – to adapt the work
Under the following conditions:
attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
https://creativecommons.org/licenses/by/4.0CC BY 4.0 Creative Commons Attribution 4.0 truetrue
Information
Captions
Convolutional layers only face a limited preceptive field and all neurons share the same weights (cf. left side of the figure). Pooling layers reduce the total input size.