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CNN 을 사용하여 단일 이미지에서 상위 수준의 헤어스타일 속성을 분류하고 회귀 학습
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Advisor
신현준
Affiliation
아주대학교 일반대학원
Department
일반대학원 라이프미디어협동과정
Publication Year
2020-02
Publisher
The Graduate School, Ajou University
Keyword
annotationattributesclassificationdata generationdeep convolutional neural networkdeep learninghairregression
Description
학위논문(석사)--아주대학교 일반대학원 :라이프미디어협동과정,2020. 2
Alternative Abstract
We present a fully automatic framework that classifies and regress the high-level hair attributes specifically length of hair and hair color from a single input image. This research was conducted to reduce the hard labor preparing the desired data for training and learning purpose. Also, this research can expand to different human face analysis research. We created new annotations for ten thousand image data. Which can be used for future research on human face analysis. We developed an automatic file distributor when annotations are liable. We further show the effectiveness of our experiment on cellular phone taken images.
Language
eng
URI
https://dspace.ajou.ac.kr/handle/2018.oak/19488
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Type
Thesis
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