C语言程序设计
数据库原理
论文
[1] Yinghui Zhang; Bo Sun; Jun He; Lejun Yu; Xiaochong Zhao ; Multi-level neural prompt for zero-shot weakly supervised group activity recognition, Neurocomputing, 2024, 571(5): 127135-127145. (SCI, JCR 二区)
[2] Zhang Y, Hu W, Sun B, et al. CoConGAN: Cooperative contrastive learning for few-shot cross-domain heterogeneous face translation[J]. Neural Computing and Applications, 2023: 1-14. (SCI, JCR 二区)
[3] Sun B, Li H, He J, Zhang Y. Supervised Contrastive Learned Deep Model for Question Continuation Evaluation[J]. IEEE Transactions on Human-Machine Systems, 2023. (SCI, JCR 二区)
[4] Zhang Y, Yu L, Sun B, et al. ENG-Face: cross-domain heterogeneous face synthesis with enhanced asymmetric CycleGAN[J]. Applied Intelligence, 2022: 1-13. (SCI, JCR 二区)
[5] Wang W, Wang Z, Zhang Y, et al. Learning Order Parameters from Videos of Skyrmion Dynamical Phases with Neural Networks[J]. Physical Review Applied, 2021, 16(1): 014005. (SCI, JCR 二区)
[6] Bo Sun#, Yinghui Zhang, J. He, Yongkang Xiao, R. Xiao. An automatic diagnostic network using skew-robust adversarial discriminative domain adaptation to evaluate the severity of depression. Computer Methods and Programs in Biomedicine. Jan. 2019.(SCI, JCR 一区, 导师一作,本人二作)
[7] Zhang Y, Sun B, Xiao Y, et al. Feature augmentation for imbalanced classification with conditional mixture WGANs. [J]. Signal Processing: Image Communication, 2019. (SCI, JCR 二区, 本人一作)
[8] YingHui Zhang, YiJia Zhao, Bo Sun, Jun He. Visualizing the prediction of laser cleaning: a dynamic preview method with multi-scale conditional generative adversarial network. [J]. Applied Optics, 2019.(SCI, JCR 二区, 本人一作)
[9] Sun B , Xu C , Jun H , LeJun Y, Zhang Y. Cleanliness prediction of rusty iron in laser cleaning using convolutional neural network. [J]. APPLIED PHYSICS A-MATERIALS SCIENCE & PROCESSING, 2019. (SCI, JCR 三区)
[10] Bo Sun, Zeng Yao, Yinghui Zhang, Lejun Yu. Local Relation Network with Multilevel Attention for Visual Question Answering. [J]. Journal of Visual Communication and Image Representation, 2019. (SCI, JCR 三区)
[11] Bo Sun, Chang Xu, Jun He, Lejun Yu, Yinghui Zhang. Cleanliness prediction of rusty iron in laser cleaning using convolutional neural networks. [J]. Applied Physics A, 2020. (SCI, JCR 三区)
[12] 张迎辉, 聂燕敏, 孙波, et al. 基于深度森林多模态数据决策级融合抑郁症评价方法[J]. 北京师范大学学报(自然科学版), 2018, 54(05):50-55.(CSCD)
专著
[1] 张迎辉,徐其华,《解问题学编程程小序一家自驾游》,电子工业出版社,2021年
会议
[1] Yinghui Zhang; Chun Liu; Bo Sun; Jun He; Lejun Yu ; NIR-VIS Heterogeneous Face Synthesis via Enhanced Asymmetric CycleGAN, International Joint Conference on Neural Networks, Online, 2021-7-18至2021-7-22. (IJCNN, CCF-C类会议)
[2] Sun B , Zhang Y , He J , et al. [ACM Press the 7th Annual Workshop - Mountain View, California, USA (2017.10.23-2017.10.23)] Proceedings of the 7th Annual Workshop on Audio/Visual Emotion Challenge, - AVEC \"17 - A Random Forest Regression Method With Selected-Text Feature For Depression Assessment[C]// Workshop on Audio/visual Emotion Challenge. ACM, 2017:61-68.(ACM会议)
专利
[1] 专利名称:“基于文生图数据增强模型的非言语行为识别方法和装置”,中国,发明专利,专利号:202311650373.9,申请日:2023年12月5日;申请人:北京师范大学;发明人:孙波、张迎辉、何珺、徐子平;
[2] 专利名称:“中学生物实验操作测评方法、装置、电子设备及存储介质”,中国,发明专利,专利号:202410399294.3,申请日:2024年4月3日;申请人:刘慧明、张迎辉、何珺、孙波;
[3] 专利名称:“一种基于自然引导和数据增强的违禁物品检测方法及系统”,中国,发明专利,专利号:202210683874.6,申请日:2022年6月17日;申请人:北京师范大学;发明人:孙波、何珺、张迎辉、钟阳财、刘筠;
[4] 专利名称:“引入多重文本关系的阅读理解试题难度自动预测方法”,中国,发明专利,专利号:202110950774.9,申请日:2021年8月18日;申请人:北京师范大学;发明人:何珺、张迎辉、孙波、余乐军、彭丽;
[5] 专利名称:“融合答题记录和题目语义的深度知识追踪模型”,中国,发明专利,专利号:2021111273766.3,申请日:2022年1月28日;申请人:北京师范大学;发明人:张迎辉、孙波、肖融、肖永康、郑瑞丽、何珺;
[6] 专利名称:“可持续学习的任务交互智能检测方法、系统及可存储介质”,中国,发明专利,专利号:202210240443.2,申请日:2022年3月10日;申请人:北京师范大学;发明人:何珺、孙波、卢思旭、张迎辉、余乐军;
[7] 专利名称:“激光清洗效果预览方法及装置”,发明人:何珺、张迎辉、孙波、余乐军,发明专利,专利号:ZL2019105757724.1;授权公告日期:2021年6月1日;
[8] 专利名称:“激光清洗参数生成方法及装置”, 发明人:孙波、何珺、余乐军、徐畅、张迎辉, 发明专利,专利号:ZL201910575762.7;授权公告日:2021年4月27日;
重要学术报告
[1] 2017.10.22-2017.10.27 A Random Forest Regression Method With Selected-Text Feature For Depression Assessment. ACM Press the 7th Annual Workshop - Mountain View, California, USA.