Back to results
US 12,738,014 B2Granted
Directed inferencing using input data transformations
AssigneeNVIDIA Corporation
InventorShekhar Dwivedi
Life of this patent
Estimating the term…
Abstract
Apparatuses, systems, and techniques to segment a region of interest in an input data for a machine learning model by obtaining a plurality of progressively compressed representations of the input data and processing at least two of the compressed representations to obtain matching locations of a region of interest of the input data.
Claims20
A method comprising:
- generating a plurality of compressed representations of an input image;
- processing, in parallel, the plurality of compressed representations of the input image using a plurality of machine learning models (MLMs), wherein a respective MLM of the plurality of MLMs is used to process a respective compressed representation of the plurality of compressed representations of the input image to estimate a location of a region of interest (ROI) in the respective compressed representation of the input image, and wherein a number of neurons in an input layer of the respective MLM corresponds to a number of pixels of the respective compressed representation;
- and
- responsive to at least a predetermined number of the estimated locations of the ROI satisfying a matching condition, generating an image of the ROI based on the input image and one or more of the estimated locations.
1 more element
A system comprising:
- one or more processing devices to:
- generate a plurality of compressed representations of an input image;
- process, in parallel, the plurality of compressed representations of the input image using a plurality of machine learning models (MLMs), wherein a respective MLM of the plurality of MLMs is used to process a respective compressed representation of the plurality of compressed representations of the input image to estimate a location of a region of interest (ROI) in the respective compressed representation of the input image, and wherein a number of neurons in an input layer of the respective MLM corresponds to a number of pixels of the respective compressed representation;
- and
- responsive to at least a predetermined number of the estimated locations of the ROI satisfying a matching condition, generate an image of the ROI based on the input image and one or more of the estimated locations.
2 more elements
A processor comprising:
- one or more processing units to:
- generate a plurality of compressed representations of an input image;
- process, in parallel, the plurality of compressed representations of the input image using a plurality of machine learning models (MLMs), wherein a respective MLM of the plurality of MLMs is used to process a respective compressed representation of the plurality of compressed representations of the input image to estimate a location of a region of interest (ROI) in the respective compressed representation of the input image, and wherein a number of neurons in an input layer of the respective MLM corresponds to a number of pixels of the respective compressed representation;
- and
- responsive to at least a predetermined number of the estimated locations of the ROI satisfying a matching condition, generate an image of the ROI based on the input image and one or more of the estimated locations.
2 more elements
Dependencies are inferred from the claim text.