Explainable AI in Art
Author:
Affiliation:
1. Graduate School of Sociology, Keio University
Publisher
Japan Society of Kansei Engineering
Link
https://www.jstage.jst.go.jp/article/isase/ISASE2024/0/ISASE2024_1_9/_pdf
Reference14 articles.
1. [1] W. R. Tan, C. S. Chan, H. E. Aguirre, and K. Tanaka; Ceci n'est pas une pipe: A Deep Convolutional Network for Fine-Art Paintings Classification, 2016 IEEE International Conference on Image Processing (ICIP), pp. 3703-3707, IEEE, 2016.
2. [2] A. Lecoutre, B. Negrevergne and F. Yger; Recognizing Art Style Automatically in Painting with Deep Learning, Asian Conference on Machine Learning, pp. 327-342, PMLR, 2017.
3. [3] L. Zhang, L. Zhang and B. Du; Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art, IEEE Geoscience and Remote Sensing Magazine, 4(2), pp. 22-40, 2016.
4. [4] E. J. Crowley and A. Zisserman; The Art of Detection, Computer Vision–ECCV 2016 Workshops: Amsterdam, the Netherlands, October 8-10 and 15-16, Proceedings, Part I 14, pp. 721-737, Springer International Publishing, 2016.
5. [5] Y. Zeng, Y. Gong and X. Zeng; Controllable digital restoration of ancient paintings using convolutional neural network and nearest neighbor, Pattern Recognition Letters, 133, pp. 158-164, 2020.
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