Invention Grant
- Patent Title: System and method for a unified architecture multi-task deep learning machine for object recognition
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Application No.: US15224487Application Date: 2016-07-29
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Publication No.: US10032067B2Publication Date: 2018-07-24
- Inventor: Mostafa El-Khamy , Arvind Yedla , Marcel Nassar , Jungwon Lee
- Applicant: Samsung Electronics Co., Ltd.
- Applicant Address: KR
- Assignee: SAMSUNG ELECTRONICS CO., LTD.
- Current Assignee: SAMSUNG ELECTRONICS CO., LTD.
- Current Assignee Address: KR
- Agency: Renaissance IP Law Group LLP
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06T7/00

Abstract:
A system to recognize objects in an image includes an object detection network outputs a first hierarchical-calculated feature for a detected object. A face alignment regression network determines a regression loss for alignment parameters based on the first hierarchical-calculated feature. A detection box regression network determines a regression loss for detected boxes based on the first hierarchical-calculated feature. The object detection network further includes a weighted loss generator to generate a weighted loss for the first hierarchical-calculated feature, the regression loss for the alignment parameters and the regression loss of the detected boxes. A backpropagator backpropagates the generated weighted loss. A grouping network forms, based on the first hierarchical-calculated feature, the regression loss for the alignment parameters and the bounding box regression loss, at least one of a box grouping, an alignment parameter grouping, and a non-maximum suppression of the alignment parameters and the detected boxes.
Public/Granted literature
- US20170344808A1 SYSTEM AND METHOD FOR A UNIFIED ARCHITECTURE MULTI-TASK DEEP LEARNING MACHINE FOR OBJECT RECOGNITION Public/Granted day:2017-11-30
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