Invention Grant
- Patent Title: Multi-task learning for dense object detection
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Application No.: US17001524Application Date: 2020-08-24
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Publication No.: US11120307B2Publication Date: 2021-09-14
- Inventor: Chensu Xie
- Applicant: MEMORIAL SLOAN KETTERING CANCER CENTER
- Applicant Address: US NY New York
- Assignee: MEMORIAL SLOAN KETTERING CANCER CENTER
- Current Assignee: MEMORIAL SLOAN KETTERING CANCER CENTER
- Current Assignee Address: US NY New York
- Agency: Foley & Lardner LLP
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06K9/00 ; G06T7/00

Abstract:
Presented herein are systems and methods for feature detection in images. A computing system may identify a biomedical image having features. The computing system may apply the biomedical image to a feature detection model. The feature detection model may include an encoder-decoder block to generate a feature map corresponding to the biomedical image, a confidence map generator having a second set of parameters to generate a confidence map using the feature map, and a localization map generator to generate a localization map using the feature map. The computing system may generate a resultant map based on the confidence map and the localization map. The resultant map identifying one or more points corresponding to the one or more features. The computing system may provide the one or more points identified in the resultant map for the biomedical image.
Public/Granted literature
- US20210056361A1 MULTI-TASK LEARNING FOR DENSE OBJECT DETECTION Public/Granted day:2021-02-25
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