Figure 2 from Andreas Maier, Christopher Syben. Tobias Lasser. Christian Riess. "A gentle introduction to deep learning in medical image processing". Zeitschrift für Medizinische Physik
<p>Volume 29, Issue 2, May 2019, Pages 86-101. <a rel="nofollow" class="external free" href="https://www.sciencedirect.com/science/article/pii/S093938891830120X#fig0010">https://www.sciencedirect.com/science/article/pii/S093938891830120X#fig0010</a>
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Original Caption: Neurons are inspired by biological neurons shown on the left. The resulting computational neuron computes a weighted sum of its inputs which is then processed by an activation function h(x) to determine the output value (cf. Fig. 5). Doing so, we are able to model linear decision boundaries, as the weighted sum can be interpreted as a signed distance to the decision boundary, while the activation determines the actual class membership. On the right-hand side, the XOR problem is shown that cannot be solved by a single linear classifier. It typically requires either curved boundaries or multiple lines.
Andreas Maier
CC BY 4.0
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