Invention Grant
- Patent Title: Age and gender estimation using small-scale convolutional neural network (CNN) modules for embedded systems
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Application No.: US15724256Application Date: 2017-10-03
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Publication No.: US10558908B2Publication Date: 2020-02-11
- Inventor: Xing Wang , Mehdi Seyfi , Minghua Chen , Him Wai Ng , Jiannan Zheng , Jie Liang
- Applicant: AltumView Systems Inc.
- Applicant Address: CA Port Moody, BC
- Assignee: AltumView Systems Inc.
- Current Assignee: AltumView Systems Inc.
- Current Assignee Address: CA Port Moody, BC
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06N3/04 ; G06K9/46 ; G06K9/62 ; G06T7/11 ; G06T7/246 ; G06K9/20 ; G06N3/06 ; G06N3/08 ; G06T5/50

Abstract:
Embodiments described herein provide various examples of an age and gender estimation system capable of performing age and gender classifications on face images having sizes greater than the maximum number of input pixels supported by a given small-scale hardware convolutional neural network (CNN) module. In some embodiments, the proposed age and gender estimation system can first divide a high-resolution input face image into a set of image patches with judiciously designed overlaps among neighbouring patches. Each of the image patches can then be processed with a small-scale CNN module, such as the built-in CNN module in Hi3519 SoC. The outputs corresponding to the set of image patches can be subsequently merged to obtain the output corresponding to the input face image, and the merged output can be further processed by subsequent layers in the age and gender estimation system to generate age and gender classifications for the input face image.
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