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US 12,762,664 B2Granted
System, devices and/or processes for application of machine learning to image anti-aliasing
AssigneeArm Limited
InventorsLiam James O'Neil, Joshua James Sowerby, Matthew James Wash, Samuel James Edward Martin
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Abstract
Example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, techniques to select between and/or among multiple available alternative approaches to perform a temporal anti-aliasing operation in processing an image.
Claims20
A method of training a neural network, comprising:
- executing a training iteration to update parameters of a neural network to predict image signal intensity values of an image frame,
- wherein executing the training iteration comprises:
- executing the neural network for multiple inferences stages, each inference stage to process image signal intensity values of an associated input image frame in a temporal sequence of image frames to provide a prediction of image values of an associated predicted image frame in the temporal sequence;
- and
- for at least one of the multiple inference stages, processing image values of a predicted image frame computed in a previous inference stage as input values in combination with image signal values of an input image frame associated with the at least one of the multiple inference stages to compute a prediction of image values of an image frame in the temporal sequence associated with the at least one of the multiple inference stages.
2 more elements
A computing device, comprising:
- a memory device;
- and
- one or more processors couple to the memory device to:
- execute a training iteration to update parameters of a neural network to predict image signal intensity values of an image frame,
- wherein execution of the training iteration comprises:
- execution of the neural network for multiple inferences stages, each inference stage to process image signal intensity values of an associated input image frame in a temporal sequence of image frames to provide a prediction of image values of an associated predicted image frame in the temporal sequence;
- and
- for at least one of the multiple inference stages, process image values of a predicted image frame computed in a previous inference stage as input values in combination with image signal values of an input image frame associated with the at least one of the multiple inference stages to compute a prediction of image values of an image frame in the temporal sequence associated with the at least one of the multiple inference stages.
5 more elements
An article, comprising:
- a non-transitory storage medium having stored thereon computer-readable instructions that are executable by one or more processors of a computing device to:
- execute a training iteration to update parameters of a neural network to predict image signal intensity values of an image frame,
- wherein execution of the training iteration comprises:
- execution of the neural network for multiple inferences stages, each inference stage to process image signal intensity values of an associated input image frame in a temporal sequence of image frames to provide a prediction of image values of an associated predicted image frame in the temporal sequence;
- and
- for at least one of the multiple inference stages, process image values of a predicted image frame computed in a previous inference stage as input values in combination with image signal values of an input image frame associated with the at least one of the multiple inference stages to compute a prediction of image values of an image frame in the temporal sequence associated with the at least one of the multiple inference stages.
3 more elements
Dependencies are inferred from the claim text.