Invention Publication
- Patent Title: METHODS AND APPARATUS FOR EXPLAINABLE MULTI-SCALE GAUSSIAN MIXTURE MODEL DISTANCE
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Application No.: US18677473Application Date: 2024-05-29
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Publication No.: US20240320953A1Publication Date: 2024-09-26
- Inventor: Anthony Rhodes , Ilke Demir , Yali Bian
- Applicant: Intel Corporation
- Applicant Address: US CA Santa Clara
- Assignee: Intel Corporation
- Current Assignee: Intel Corporation
- Current Assignee Address: US CA Santa Clara
- Main IPC: G06V10/74
- IPC: G06V10/74 ; G06V10/46

Abstract:
An example apparatus includes interface circuitry, machine-readable instructions, and at least one processor circuit to be programmed by the machine-readable instructions to access a first saliency map and a second saliency map associated with an image dataset, encode pixel-level intensity of the first saliency map, encode pixel-level intensity of the second saliency map, generate a saliency comparison metric based on the pixel-level intensity of the first saliency map and the pixel-level intensity of the second saliency map, and compare spatial properties of the first saliency map and the second saliency map using the saliency comparison metric.
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