Method and system for image segmentation using controlled feedback
AssigneeKonica Minolta Laboratory U.S.A., Inc.
InventorsSachin Mehta, Haisong Gu
Life of this patent
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Abstract
A method, a computer readable recording medium, and a system are disclosed for image segmentation using controlled feedback in a neural network. The method includes extracting image data from an image; performing one or more semantic segmentations on the extracted image data; introducing one or more classifiers to each of the one or more semantic segmentations, each of the one or more classifiers assigning a probability to one or more classes of objects within the image; and generating a segmentation mask from the one or more semantic segmentations.
Claims20
A method for image segmentation using controlled feedback in a neural network, the method comprising:
- extracting image data from an image;
- performing one or more semantic segmentations on the extracted image data;
- introducing one or more classifiers to each of the one or more semantic segmentations, each of the one or more classifiers assigning a probability to one or more classes of objects within the image;
- and
- generating a segmentation mask from the one or more semantic segmentations.
A non-transitory computer readable recording medium stored with a computer readable program code for image segmentation using controlled feedback in a neural network, the computer readable program code configured to execute a process comprising:
- extracting image data from an image;
- performing one or more semantic segmentations on the extracted image data;
- introducing one or more classifiers to each of the one or more semantic segmentations, each of the one or more classifiers assigning a probability to one or more classes of objects within the image;
- and
- generating a segmentation mask from the one or more semantic segmentations.
A system for image segmentation using controlled feedback in a neural network, the system comprising:
- a processor;
- and
- a memory storing instructions that, when executed, cause the system to:
- extract image data from an image;
- perform one or more semantic segmentations on the extracted image data;
- introduce one or more classifiers to each of the one or more semantic segmentations, each of the one or more classifiers assigning a probability to one or more classes of objects within the image;
- and
- generate a segmentation mask from the one or more semantic segmentations.
Dependencies are inferred from the claim text.