基本介紹
主要成就,獲獎記錄,社會任職,
主要成就
1.Tong, S. (2021). Informatics Approaches for Understanding Human Facial Attractiveness Perception and Visual Attention. （博士論文）
二、計算機視覺技術輔助結構化網路數據的知覺行為及風格的表達，用於評估情緒與知覺風格的關係。該研究涉及的領域有：計算認知科學研究範式轉變、旅遊資源挖掘及情緒拓展理論。
2.Tong, S., Loh, Y. P., Liang, X., & Kumada, T. (2019). Wide or narrow? A visual attention inspired model for view-type classification. IEEE Access, 7, 48725-48738. (SCI/SSCI)
3.Liu, Y., Liang, X., Tong, S., & Kumada, T. (2019, September). Photo shot-type disambiguation by multi-classifier semi-supervised learning. In 2019 IEEE International Conference on Image Processing (ICIP) (pp. 2466-2470). IEEE. (CCF推薦會議)
4.Liang, X., Tong, S., Kumada, T., & Loh, Y. P. (2019, July). Understanding the Photo-shooting Patterns of Sightseeing. In Proceedings of the 2019 2nd International Conference on Data Science and Information Technology (pp. 36-41).
5.Liang, X., Fan, L., Loh, Y. P., Liu, Y., & Tong, S. (2017). Happy travelers take big pictures: A psychological study with machine learning and big data. arXiv preprint arXiv:1709.07584. (Google Travel and Conference Scholarship)
6.Peng Loh, Y., Tong, S., Liang, X., Kumada, T., & Seng Chan, C. (2017). Understanding scenery quality: A visual attention measure and its computational model. In Proceedings of the IEEE International Conference on Computer Vision Workshops (pp. 289-297). (CCF推薦會議)
7.Tong, S., Loh, Y. P., Liang, X., & Kumada, T. (2016, September). Visual attention inspired distant view and close-up view classification. In 2016 IEEE International Conference on Image Processing (ICIP) (pp. 2787-2791). IEEE. (CCF推薦會議)
一 、計算機視覺技術可以從自然瞬態圖像的特徵有意義的語義特徵，用於理解人類對面孔美學的認知過程。該研究涉及的領域有：計算神經科學的研究範式轉變、美學計算及可解釋AI。
8.Tong, S., Liang, X., Kumada, T., & Iwaki, S. (2021). Putative ratios of facial attractiveness in a deep neural network. Vision Research, 178, 86-99. (SCI/SSCI)
9.Liang, X., Tong, S., Kumada, T., & Iwaki, S. (2019, September). Golden ratio: The attributes of facial attractiveness learned by CNN. In 2019 IEEE International Conference on Image Processing (ICIP) (pp. 2124-2128). IEEE. (CCF推薦會議)
10.Tong, S., Liang, X., Kumada, T., Iwaki, S., & Tosa, N. (2017, September). Learning the cultural consistent facial aesthetics by convolutional neural network. In 2017 International Conference on Culture and Computing (Culture and Computing) (pp. 97-103). IEEE.
三、圖像處理、圖像融合研究
11.Yang, Y., Tong, S., Huang, S., Lin, P., & Fang, Y. (2017). A hybrid method for multi-focus image fusion based on fast discrete curvelet transform. IEEE Access, 5, 14898-14913. (SCI)
12.楊勇, 童松, 黃淑英. (2015). 快速離散 Curvelet 變換域的圖像融合. 中國圖象圖形學報, 20(2), 219-228.
13.Yang, Y., Tong, S., Huang, S., & Lin, P. (2014). Multifocus image fusion based on NSCT and focused area detection. IEEE Sensors Journal, 15(5), 2824-2838. (SCI)
14.Yang, Y., Tong, S., Huang, S., & Lin, P. (2014). Dual-tree complex wavelet transform and image block residual-based multi-focus image fusion in visual sensor networks. Sensors, 14(12), 22408-22430. (SCI)
15.Yang, Y., Tong, S., Huang, S., & Lin, P. (2014). Log-Gabor energy based multimodal medical image fusion in NSCT domain. Computational and mathematical methods in medicine, 2014. (SCI)
16.楊勇, 童松, 黃淑英, 方誌軍, 楊壽淵. (2014). 一種 NSCT 域多聚焦圖像融合新方法. 圖學學報, 35(6), 854-863.
其它感興趣的研究包括：“美育的遷移效應（芭蕾舞）”、“創造力的評估與計算”、“音樂的文化進化”、“情緒傳播”及“歸因的文化差異”等。
獲獎記錄
2022-2024，2021年國家“博士後國際交流計畫”引進項目入選者；
2022-2024，清華大學“水木學者”；
2022-2024，清華大學“支持基礎文科”博士後；
2017，IEEE國際文化與計算會議委員會, 優秀論文提名獎；
2016，日本電氣通信財團，旅費援助金；
2016-2021，教育部留學基金（CSC）公派讀博獎學金；
研究生優秀科研成果獎勵（2014、2015）；優秀研究生；研究生優秀創新計畫（2014）。
社會任職
審稿人：Human Brain Mapping、IEEE Transactions on Biomedical Engineering、IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing、IEEE Sensors Journal、Neural Computing and Application等。
IEEE 會員；IEEE青年學者；圖象圖形學會會員
