Neural Network - Revision history

Frank@tygron.nl: Redirected page to Neural Network (Inference Overlay)

2024-10-08T14:30:31Z

Redirected page to Neural Network (Inference Overlay)

← Older revision		Revision as of 14:30, 8 October 2024
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	A Neural Network in the {{software}} is a pre-trained network that can be used by an [[Inference Overlay\|AI 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.~~

	~~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.~~


	~~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]].~~

	~~{{article end~~
	~~\|seealso=~~
	* [[Inference Overlay]]
	* [[ONNX]]
	* [[PyTorch]]
	}}

	~~==References==~~
	~~<references>~~
	~~<ref name="ONNX">ONNX ∙ found at: https://onnx.ai/ (last visited: 2024-09-21)</ref>~~
	~~<ref name="Cheatsheet">Cheatsheet ∙ found at: https://stanford.edu/~shervine/teaching/cs-230/cheatsheet-convolutional-neural-networks (last visited: 2024-09-21)</ref>~~
	~~</references>~~

Maxim@tygron.com at 12:10, 30 September 2024

2024-09-30T12:10:25Z

← Older revision		Revision as of 12:10, 30 September 2024
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	A Neural Network in the {{software}} is a pre-trained network that can be used by an [[AI Inference Overlay\|Inference Overlay]] to classify or detect patterns and features given one or more input [[Overlay]]s.		A Neural Network in the {{software}} is a pre-trained network that can be used by an [[Inference Overlay\|AI Inference Overlay]] to classify or detect patterns and features given one or more input [[Overlay]]s.
	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.		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.

Maxim@tygron.com at 12:10, 30 September 2024

2024-09-30T12:10:16Z

← Older revision		Revision as of 12:10, 30 September 2024
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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.		A Neural Network in the {{software}} is a pre-trained network that can be used by an [[AI Inference Overlay\|Inference Overlay]] to classify or detect patterns and features given one or more input [[Overlay]]s.
	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.		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.

Maxim@tygron.com: /* References */

2024-09-30T12:09:52Z

References

← Older revision		Revision as of 12:09, 30 September 2024
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	<references>		<references>
	<ref name="ONNX">ONNX ∙ found at: https://onnx.ai/ (last visited: 2024-09-21)</ref>		<ref name="ONNX">ONNX ∙ found at: https://onnx.ai/ (last visited: 2024-09-21)</ref>
	<ref name="Cheatsheet">Cheatsheet ∙ found at: https://stanford.edu/~shervine/teaching/cs-230/cheatsheet-convolutional-neural-networks</ref>		<ref name="Cheatsheet">Cheatsheet ∙ found at: https://stanford.edu/~shervine/teaching/cs-230/cheatsheet-convolutional-neural-networks (last visited: 2024-09-21)</ref>
	</references>		</references>

Maxim@tygron.com at 12:09, 30 September 2024

2024-09-30T12:09:18Z

← Older revision		Revision as of 12:09, 30 September 2024
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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.		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.
	Neural Networks are stored in the {{software}} as data [[item]]s with a reference to an [[ONNX]]-file (Open Neural Network Exchange format).		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.

	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.		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.


	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]].		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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	* [[PyTorch]]		* [[PyTorch]]
	}}		}}

			==References==
			<references>
			<ref name="ONNX">ONNX ∙ found at: https://onnx.ai/ (last visited: 2024-09-21)</ref>
			<ref name="Cheatsheet">Cheatsheet ∙ found at: https://stanford.edu/~shervine/teaching/cs-230/cheatsheet-convolutional-neural-networks</ref>
			</references>

Maxim@tygron.com at 09:38, 25 September 2024

2024-09-25T09:38:32Z

← Older revision		Revision as of 09:38, 25 September 2024
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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.		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.

	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.		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]].

	{{article end		{{article end
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	* [[Inference Overlay]]		* [[Inference Overlay]]
	* [[ONNX]]		* [[ONNX]]
			* [[PyTorch]]
	}}		}}

Maxim@tygron.com at 09:32, 25 September 2024

2024-09-25T09:32:00Z

← Older revision		Revision as of 09:32, 25 September 2024
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	{{article end		{{article end
	\|seealso=[[Inference Overlay]] [[ONNX]]		\|seealso=
			* [[Inference Overlay]]
			* [[ONNX]]
	}}		}}

Maxim@tygron.com at 09:31, 25 September 2024

2024-09-25T09:31:44Z

← Older revision		Revision as of 09:31, 25 September 2024
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	{{article end		{{article end
	\|seealso=*[[Inference Overlay]]		\|seealso=[[Inference Overlay]] [[ONNX]]
	~~\|seealso=~~*[[ONNX]]
	}}		}}

Maxim@tygron.com at 09:31, 25 September 2024

2024-09-25T09:31:25Z

← Older revision		Revision as of 09:31, 25 September 2024
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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.		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.

	Whether a Neural Network classifies or detects objects given an input depends on its inference model. Such a model consists ~~ousing~~ AI-software, such as PyTorch.		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.

	{{article end		{{article end

Maxim@tygron.com at 09:31, 25 September 2024

2024-09-25T09:31:17Z

← Older revision		Revision as of 09:31, 25 September 2024
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	{{article end		{{article end
	\|seealso=*[[Inference Overlay]]		\|seealso=*[[Inference Overlay]]
			\|seealso=*[[ONNX]]
	}}		}}