文章詳目資料
Journal of Computers EIMEDLINEScopus
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| 篇名 | Good Portrait Selection Based on Deep Learning Using Facial Expressions |
|---|---|
| 卷期 | 29:6 |
| 作者 | Umer Waqas 、 Tae-Young Choe |
| 頁次 | 132-139 |
| 關鍵字 | convolution neural networks 、 deep learning 、 facial expressions 、 image processing 、 photo psychology 、 picture selection 、 EI 、 MEDLINE 、 Scopus |
| 出刊日期 | 201812 |
| DOI | 10.3966/199115992018122906012 |
中文摘要
英文摘要
This paper suggests an algorithm to choose good pictures among a bundle of pictures. Since it is very hard to collect private selections of good images from people, the paper divides facial expressions into ten categories, and add ‘good’ tags to photos included in some categories like wink or grin. The proposed algorithm uses convolution neural networks (CNN) to classify the pictures as good or not. The experimental results show that the accuracy of the algorithm is 97.15%, and average execution time is 0.3 seconds. For application purposes, the proposed algorithm is further applied to a group photo in order to count the number of faces that look good.
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