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Personal profile

Research Interests

computer vision, machine learning, artificial intelligence, deep learning

Education/Academic qualification

PhD, National Taiwan University

Sep 2005Oct 2010

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Projects

Developing Deep Instance Segmentation Algorithms for Video Surveillance

Lin, Y.

1/08/2031/07/21

Project: Government MinistryMinistry of Science and Technology

Co-Occurrence Deep Network Learning for Unsupervised Common Pattern Detection

Lin, Y.

1/08/2031/07/21

Project: Government MinistryMinistry of Science and Technology

Deep Learning Networks for Applications with Limited Labeling Data

Lin, Y.

1/01/2031/12/20

Project: Government MinistryMinistry of Science and Technology

Developing Deep Instance Segmentation Algorithms for Video Surveillance

Lin, Y.

1/08/2231/07/23

Project: Government MinistryMinistry of Science and Technology

Developing Deep Instance Segmentation Algorithms for Video Surveillance

Lin, Y.

1/08/2131/07/22

Project: Government MinistryMinistry of Science and Technology

Research Output

Deep Co-Saliency Detection via Stacked Autoencoder-Enabled Fusion and Self-Trained CNNs

Tsai, C. C., Hsu, K. J., Lin, Y-Y., Qian, X. & Chuang, Y. Y., Apr 2020, In : IEEE Transactions on Multimedia. 22, 4, p. 1016-1031 16 p., 8809285.

Research output: Contribution to journalArticle

  • DGGAN: Depth-image guided generative adversarial networks for disentangling RGB and depth images in 3D hand pose estimation

    Chen, L., Lin, S. Y., Xie, Y., Lin, Y. Y., Fan, W. & Xie, X., Mar 2020, Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020. Institute of Electrical and Electronics Engineers Inc., p. 400-408 9 p. 9093380. (Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Referring expression object segmentation with caption-aware consistency

    Chen, Y. W., Tsai, Y. H., Wang, T., Lin, Y. Y. & Yang, M. H., 2020.

    Research output: Contribution to conferencePaper

    TAGAN: Tonality-alignment generative adversarial networks for realistic hand pose synthesis

    Chen, L., Lin, S. Y., Xie, Y., Tang, H., Xue, Y., Lin, Y. Y., Xie, X. & Fan, W., 2020.

    Research output: Contribution to conferencePaper

  • 1 Scopus citations

    VOSTR: Video Object Segmentation via Transferable Representations

    Chen, Y. W., Tsai, Y. H., Lin, Y-Y. & Yang, M. H., 1 Apr 2020, In : International Journal of Computer Vision. 128, 4, p. 931-949 19 p.

    Research output: Contribution to journalArticle