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- W4285193811 abstract "The set of algorithms designed for modeling a task by using multiple levels of nonlinear and nested operation units called artificial neurons falls under the umbrella of deep learning. Deep neural networks have found massive applications in the biomedical as, for instance, biomedical images and gene-expression analysis, genomics, and transcriptomics. This chapter introduces the artificial neuron model and some bases related to feedforward artificial neural networks. We will also discuss one of the central aspects of the popularity and power of deep learning, which is how a new latent representation of the input is learned by the network. Finally, we will provide a taste of the architecture of CNN." @default.
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- W4285193811 date "2022-01-01" @default.
- W4285193811 modified "2023-09-27" @default.
- W4285193811 title "Deep learning" @default.
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- W4285193811 doi "https://doi.org/10.1016/b978-0-12-822952-1.00014-0" @default.
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