Earticle

초록

영어

Photograph aesthetical evaluation has been widely investigated in these decades. The most used assessing methods are mainly classical data mining methods such as SVM, ANN(Artificial Neural Network), linear programming and so on. In this paper, we presented a method based on artificial neural network and deep learning methods which is also a hot research topic recently. We downloaded a medium and a large dataset from a well-known online photograph portal and trained on them. Results showed that the accuracy of classification was above 82.1%, which was better than all state-of-the-art methods as well as a moderate result from those methods never adopted up to now.

목차

Abstract
 1. Introduction
 2. Related work
 3. Proposed Method
  3.1. Feature extraction
  3.2. Artificial Neural Network
  3.3. Autoencoder
  3.4 Quality Assessment and Classification
 4. Experiment Result
  4.1 Database Collection
  4.2 Experimental Results
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Yimin Zhou [ College of Electronics and Information, Tongji University, Shanghai, 201804, China ]
• Guangyao Li [ College of Electronics and Information, Tongji University, Shanghai, 201804, China ]
• Yunlan Tan [ School of Electronics and Information, Jinggangshan University, Jiangxi, 343009, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605