Difference between revisions of "File:Fig2 Krantz FrontPlantSci2021 12.jpg"

Latest revision as of 22:41, 17 December 2021

Description	Figure 2. An artificial neural network. Information, i.e., x₁, x₂, and x₃, enters the network via the input layer (layer 1, blue). Weights w_ij determine the quantity by which information is passed to layer 2 (hidden, green). Processed information, here y_1n and y_2n, leaves the network by the output layer (layer n, yellow). Indices refer to neuron number and layer number, respectively. Calculations for neurons are depicted exemplarily for h₁₂ (first neuron in second layer), which is composed of a bias (b₁₂) and summed information of the previous layer, here layer 1. Resulting information, y₁₂, is passed to the next layer and might comprise nonlinearities in f(h₁₂). Deep neural networks typically comprise several and up to numerous hidden layers, indicated in grey.
Source	Krantz, M.; Zimmer, D.; Adler, S.O.; Kitashova, A.; Klipp, E.; Mühlhaus, T.; Nägele, T. (2021). "Data management and modeling in plant biology". Frontiers in Plant Science 12: 717958. doi:10.3389/fpls.2021.717958.
Date	2021
Author	Krantz, M.; Zimmer, D.; Adler, S.O.; Kitashova, A.; Klipp, E.; Mühlhaus, T.; Nägele, T.
Permission (Reusing this file)	Creative Commons Attribution 4.0 International
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+==Summary==
+{{Information
+|Description='''Figure 2.''' An artificial neural network. Information, i.e., x<sub>1</sub>, x<sub>2</sub>, and x<sub>3</sub>, enters the network via the input layer (layer 1, blue). Weights w<sub>ij</sub> determine the quantity by which information is passed to layer 2 (hidden, green). Processed information, here y<sub>1n</sub> and y<sub>2n</sub>, leaves the network by the output layer (layer n, yellow). Indices refer to neuron number and layer number, respectively. Calculations for neurons are depicted exemplarily for h<sub>12</sub> (first neuron in second layer), which is composed of a bias (b<sub>12</sub>) and summed information of the previous layer, here layer 1. Resulting information, y<sub>12</sub>, is passed to the next layer and might comprise nonlinearities in f(h<sub>12</sub>). Deep neural networks typically comprise several and up to numerous hidden layers, indicated in grey.
+|Source={{cite journal |title=Data management and modeling in plant biology |journal=Frontiers in Plant Science |author=Krantz, M.; Zimmer, D.; Adler, S.O.; Kitashova, A.; Klipp, E.; Mühlhaus, T.; Nägele, T. |volume=12 |at=717958 |year=2021 |doi=10.3389/fpls.2021.717958}}
+|Author=Krantz, M.; Zimmer, D.; Adler, S.O.; Kitashova, A.; Klipp, E.; Mühlhaus, T.; Nägele, T.
+|Date=2021
+|Permission=[http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International]
+}}
 == Licensing ==
 {{cc-by-4.0}}