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Tong, S. (2021). Informatics Approaches for Understanding Human Facial Attractiveness Perception and Visual Attention. Kyoto University. （博士论文）
计算机视觉技术辅助结构化网络数据的知觉行为及风格的表达，用于评估情绪与知觉风格的关系。该研究涉及的领域有：计算认知科学研究范式转变、旅游资源挖掘及情绪拓展理论。（计算认知行为科学方向）
Tong, S., Duan J., Liang, X., Kumada T., Peng, K. , Nakashima, T., (2023, June) “Inferring Affective Experience from the Big Picture Metaphor: A Two-dimensional Visual Breadth Model”, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, (CCF推荐会议).
Tong, S., Liang, X., Kumada, T., Zhang, P., Peng, K., (2022, December) “Detecting the Attention Scopes from Travel Photos”, In IEEE Intl. Conf. Information Technology and Biomedical Engineering (pp. 213-217). （Best Paper Award）
Tong, S., Loh, Y., Liang, X., & Kumada, T. (2019). Wide or narrow? A visual attention-inspired model for view-type classification. IEEE Access, 7, 48725-48738. (SCI/SSCI)
Tong, S., Loh, Y., 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推荐会议)
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推荐会议)
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). (导师一作)
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推荐会议)
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)
计算机视觉技术可以从自然瞬态图像的特征有意义的语义特征，用于理解人类对面孔美学的认知过程。该研究涉及的领域有：计算神经科学的研究范式转变、美学计算及可解释AI。（计算认知神经科学方向）
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)
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. （Best Honorable Mention Award）
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推荐会议, 导师一作)
图像处理、生物医学工程等研究。
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，导师一作，ESI高被引论文)
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, 导师一作)
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, 导师一作)
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, 导师一作)
杨勇, 童松, 黄淑英. (2015). 快速离散 Curvelet 变换域的图像融合. 中国图象图形学报, 20(2), 219-228. (CCF推荐期刊, 导师一作)
杨勇, 童松, 黄淑英, 方志军, 杨寿渊. (2014). 一种 NSCT 域多聚焦图像融合新方法. 图学学报, 35(6), 854-863. (CCF推荐期刊, 导师一作)
其它感兴趣的研究包括：“美育的迁移效应（芭蕾舞）”、“创造力的评估与计算”、“音乐的文化进化”、“情绪传播”、“自然疗愈”、“人工智能辅助设计”及“归因的文化差异”等。
Lee, H, Zhou, W., Bai H.H., Meng W., Zeng, T., Peng, K., Tong, S., Kumada, T., (2022, November). Natural Language Processing Algorithms for Divergent Thinking Assessment, IEEE 6th Eurasian Conference on Educational Innovation. (创造性思维计算, 通讯作者)
Zhou, X, Tong, S., Liu, R., Wang, F., Peng, K., The Impact of “Emotion Grammar” on the Veracity of News Headlines: Evidence from Machine Learning, In IEEE Intl. Conf. Information Technology and Biomedical Engineering (pp. 449-453). (情绪传播)
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