Invention Grant
- Patent Title: Method for feature data recalibration and apparatus thereof
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Application No.: US16676694Application Date: 2019-11-07
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Publication No.: US10824944B2Publication Date: 2020-11-03
- Inventor: Hyun Jae Lee
- Applicant: Lunit Inc.
- Applicant Address: KR Seoul
- Assignee: LUNIT INC.
- Current Assignee: LUNIT INC.
- Current Assignee Address: KR Seoul
- Agency: Lex IP Meister, PLLC
- Priority: com.zzzhc.datahub.patent.etl.us.BibliographicData$PriorityClaim@56558a27
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06F17/18 ; G06T3/00 ; G06N20/00

Abstract:
A method of recalibrating a feature data of each channel generated by a convolution layer of a convolution neural network is provided. According to some embodiments, since an affine transformation is applied to the feature data of each channel independently of the feature data of the other channel, the overall number of parameters defining the affine transformation is minimized. As a result, the amount of computations required in performing the feature data recalibration can be reduced.
Public/Granted literature
- US20200302290A1 METHOD FOR FEATURE DATA RECALIBRATION AND APPARATUS THEREOF Public/Granted day:2020-09-24
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