Output tensor (Inference Overlay): Difference between revisions
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An Output tensor is a multi-dimensional data array that serves as output for [[Neural Network]]s. Generally these output tensors are results of the operations applied by the convolution neural network on the [[Input tensor (Inference Overlay)|input tensors]]. Depending on the type of neural network, multiple type of output tensors can be generated. | An Output tensor is a multi-dimensional data array that serves as output for [[Region-based Convolutional Neural Network (Inference Overlay)|RCNN]]s. Generally these output tensors are results of the operations applied by the convolution neural network on the [[Input tensor (Inference Overlay)|input tensors]]. Depending on the type of neural network, multiple type of output tensors can be generated. | ||
[[File:inference_overlay_wizard_tensor_link_ouput.jpg|thumb|right|An output tensor link in the Inference Overlay Wizard.]] | [[File:inference_overlay_wizard_tensor_link_ouput.jpg|thumb|right|An output tensor link in the Inference Overlay Wizard.]] | ||
Latest revision as of 15:56, 29 June 2026
An Output tensor is a multi-dimensional data array that serves as output for RCNNs. Generally these output tensors are results of the operations applied by the convolution neural network on the input tensors. Depending on the type of neural network, multiple type of output tensors can be generated.
In the Tygron Platform, the following output tensors are supported:
Notes
- The Inference Overlay wizard will report an issue when a result type is referenced by a tensor link but is not yet added to the Inference Overlay.