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| A Neural Network in the {{software}} is a pre-trained network that can be used by an [[Inference Overlay]] to classify or detect patterns and features given one or more input [[Overlay]]s.
| | #REDIRECT [[Neural Network (Inference Overlay)]] |
| Neural Networks are stored in the {{software}} as data [[item]]s with a reference to an [[ONNX]]-file (Open Neural Network Exchange format<ref name="ONNX"/>). Multiple type of neural networks<ref name="Cheatsheet"/> are supported.
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| Input and output for neural networks is handled using data tensors. These tensors are multi-dimensional data arrays. They are automatically identified when selecting or adding a new Neural Network.
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| Whether a Neural Network classifies or detects objects given an input depends on its inference model. Such a model consists using AI-software, such as [[PyTorch]].
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| {{article end
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| |seealso=
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| * [[Inference Overlay]]
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| * [[ONNX]]
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| * [[PyTorch]]
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| }}
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| ==References==
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| <references>
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| <ref name="ONNX">ONNX ∙ found at: https://onnx.ai/ (last visited: 2024-09-21)</ref>
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| <ref name="Cheatsheet">Cheatsheet ∙ found at: https://stanford.edu/~shervine/teaching/cs-230/cheatsheet-convolutional-neural-networks</ref>
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| </references>
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Latest revision as of 14:30, 8 October 2024