姓名 | 高永彬 | 性别 | 男 | | 职称 | 副教授 | 研究方向 | 视觉SLAM技术、三维视觉分析、自然语言处理、知识图谱、无人机/无人车、智能安防、智慧医疗、智能制造 | 通讯地址 | 上海市松江区上海工程技术大学现代交通工程中心7718室 | 邮政编码 | 201620 | 联系电话 | 021-6779-1131 | 电子邮箱 | gaoyongbin@sues.edu.cn | 个人简介 |
高永彬,中共党员,博士,副教授,上海市晨光学者,上海市人才发展基金资助,现任红足—世足球网副院长(分管科研与国际交流),上海市信息学会理事,上海市计算机学会计算机视觉专委会副秘书长,上海市人工智能技术协会专家委员,上海市数据智能技术及其应用协同创新中心副主任,工业互联网产业联盟民用飞机制造与运维大数据分析实验室常务副主任,IJCAI-YES青年学术带头人。以一作/通讯发表包括IEEE TIP、IEEE TCSVT、IEEE TITS, IEEE IOTJ, ACM TOMM、ICME、ICCV等知名期刊/会议论文50余篇。主持国家级项目/省部级项目6项,并作为主要技术负责人参与国家科技部2030-新一代人工智能重大专项1项、工信部项目2项、国家基金委重点项目2项。2019年获得上海市科技进步二等奖。同时,与中国商飞、振华重工、上汽集团、广汽集团、上海肺科医院、上海长征医院、上海华东医院、复旦大学附属眼耳鼻喉医院、南方医科大学附属珠江医院等进行深入的合作,主持5项横向课题。获得2021年上海工程技术大学五四青年奖章。担任SCI期刊Applied Intelligence副主编(2021影响因子:5.086)。研究方向包括:计算机视觉、机器学习、SLAM、知识图谱、无人机/无人车、智能安防、智慧医疗、智能制造。
| 代表性项目情况 | 上海市科委“科技创新行动计划”社会发展科技攻关项目,21DZ1204900,“智能眩晕诊疗全流程数字化平台”,70万,2021.07~2024.6.30,在研,主持。 上海市地方能力建设项目,21010501500, “汽车领域知识驱动的设备故障诊断与质量检测关键技术及应用”,2021.07~2024.6,60万,在研,主持。 上海市人才发展基金资助计划, 2021002,2020.08~2023.12,30万,主持。 工信部卫健委两部门联合5G+医疗健康应用试点项目, “面向医联体的5G+远程诊断系统研发及创新应用示范”, 后补助,课题负责人。 国家自然科学基金青年项目,61802253,“单目多视角深度图估计的三维目标检测与语义重建研究”,25万,2019.01-2021.12,结题,主持。 上海市教委“晨光人才计划”,17CG59,“单目摄像头中三维目标检测与识别研究”,2018.01~2019.12,在研,主持。 上海市“科技创新行动计划”临床医学领域项目子课题, 18411952800,“基于CT影像的胃癌分期数据挖掘应用及其诊治决策智能辅助系统初构研究”,15万,2018.6.30-2021.6.30, 结题,主持。 上海市教委,上海市数据智能技术及其应用协同创新中心,2500万,在研,技术骨干。 科技创新2030—“新一代人工智能”重大项目,2020AAA0109300,工业领域知识自动构建与推理决策技术及应用,6815万,2020.11-2023.10,在研,技术骨干(排名第9)。 科技创新2030—“新一代人工智能”重大项目课题,2020AAA0109302,面向常识与专业知识的知识图谱自动抽取与构建,330万,2020.11-2023.10,在研,课题联系人。 国家基金委民航联合基金重点项目,U2033218,多源数据融合的机场道面关键参数提取和状态评估技术,210万,2021.01.01-2024.12.31,在研,参与(排名第2) 国家基金委重点项目,61831018,“自主学习的移动互联网视频传输基础理论与方法”,292万,2019.1.1-2023.12.31, 在研,合作单位。
| 代表性论文 | Yongbin Gao, Xuebing Liu, Jun Li, Zhijun Fang, Xiaoyan Jiang, Kazi Mohammed Saidul Huq, “LFT-Net: Local Feature Transformer Network for Point Clouds Analysis”, IEEE Transactions on Intelligent transportation systems(TITS), vol. 24, no. 2, 2023. (SCI, IF:9.551) Fangzheng Tian, Yongbin Gao*, Zhijun Fang, Yuming Fang, Jia Gu, Hamido Fujita, Jenq-Neng Hwang, "Depth Estimation Using A Self-Supervised Network based on Cross-layer Feature Fusion and the Quadtree Constraint," IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 32, no. 4, pp. 1751-1766, 2022. (SCI, IF:5.859) Yongbin Gao, Fangzheng Tian, Jun Li, Zhijun Fang, Saba Al-Rubaye, Wei Song, Yier Yan,“Joint Optimization of Depth and Ego-Motion for Intelligent Autonomous Vehicles,” IEEE Transactions on Intelligent transportation systems (TITS),DOI: 10.1109/TITS.2022.3159275, 2023 (SCI, IF: 9.551) Anjie Wang, Zhijun Fang, Yongbin Gao*, Songchao Tan, Shanshe Wang, Siwei Ma, Jenq-Neng Hwang, “Adversarial Learning for Joint Optimization of Depth and Ego-Motion”, IEEE Transactions on Image Processing, vol. 29, pp. 4130-4142, 2020. (SCI, IF:11.041) CCF-A类,中科院1区 Shanbao Qiao, Neal N. Xiong, Yongbin Gao*, Zhijun Fang, Wenjun Yu, Juan Zhang, Xiaoyan Jiang, “Self-Supervised Learning of Depth and Ego-motion for 3D Perception in Human Computer Interaction,” ACM Transactions on Multimedia Computing, Communications and Applications(ACM TOMM),2023, CCF-B类 Jun Li, Wei Song, Yongbin Gao*, et.al. “Monocular 3D Object Detection Based on Depth-Guided Local Convolution for Smart Payment in D2D systems”, IEEE Internet of Things Journal, vol. 10, no. 3, pp. 2245-2254, 2023. (SCI, IF:10.238) 中科院1区 Junwen Wang, Yongbin Gao*, Zhijun Fang, An Angular Shrinkage BERT model for Few-shot Relation Extraction with None-of-the-above Detection, Pattern Recognition Letters,https://doi.org/10.1016/j.patrec.2023.01.002, 2022. (SCI, IF: 4.757) Yini Wang, Yongbin Gao*, Wenjun Yu, Ruyan Guo, Weibing Wan, et al. “Transformer Networks with Adaptive Inference for Scene Graph Generation,” Applied Intelligence, accepted, 2022. (SCI, IF: 5.019) Tian, Fangzheng, Gao, Yongbin*, Fang, Zhijun, Gu Jia. Automatic coronary artery segmentation algorithm based on deep learning and digital image processing. Applied Intelligence, vol. 51, pp. 8881-8895, 2021. (SCI, IF: 5.019) CCF推荐 Renyue Dai, Yongbin Gao*, Zhijun Fang, Xiaoyan Jiang, Anjie Wang, Juan Zhang, Cengsi Zhong, “Unsupervised learning of depth estimation based on attention model and global pose optimization,” Signal Processing: Image Communication, vol. 78, pp. 284-292, 2019. (SCI, IF:3.453) CCF推荐 Yongbin Gao, Hyo Jong Lee, “Pose-invariant features and Personalized Correspondence Learning for Face Recognition,” Neural Computing and Applications, vol. 31, no.1, pp. 607-616, 2019. (SCI, IF:5.102) Yongbin Gao, Hyo Jong Lee, “Cross-Pose Face Recognition Based on Multiple Virtual Views and Alignment Error,” vol. 65, pp. 170-176, Nov. 2015, Pattern Recognition Letters. (SCI, IF: 4.757) CCF推荐 Fangzheng Tian, Yongbin Gao*, Zhijun Fang, Jia Gu, Shuqun Yang, “3D reconstruction with auto-selected keyframes based on depth completion correction and pose fusion,” Journal of Visual Communication and Image Representation, vol. 79, 2021. (SCI, IF: 2.887)CCF推荐 Yongbin Gao, Hyo Jong Lee, “Learning warps based similarity for pose-unconstrained face recognition,” Multimedia tools and applications, vol. 77, no. 2, 2018. (SCI, IF: 2.757) CCF推荐 Anjie Wang#, Yongbin Gao#, Xiaoyan Jiang, Zhijun Fang*, Shanshe Wang, Siwei Ma, Jenq-Neng Hwang. “Unsupervised learning of depth and ego-motion with spatial-temporal geometric constraints,” IEEE International Conference on Multimedia and Expo (ICME), 2019. (CCF B类会议) Jiacheng Xu, Zhijun Fang, Yongbin Gao, Siwei Ma, Yaochu Jin, Heng Zhou, Anjie Wang, “Point AE-DCGAN: A deep learning model for 3D point cloud lossy geometry compression,” Data Compression Conference, 2021. (CCF B类会议) Zhijun Fang, Yongbin Gao, Naixue Xiong, Athanasios V. Vasilakos, Yuming Fang, “A general effective rate control system based on matching measurement and inter-quantizer,” vol. 346-347, pp. 351-368, 2016, Information Sciences. (SCI, IF: 8.223) 1区 Heng Zhou, Zhijun Fang*, Yongbin Gao, Bo Huang, Cengsi Zhong, “Feature Fusion Network based on Attention Mechanism for 3D Semantic Segmentation of Point Clouds,” Pattern Recognition Letters, 2020. (SCI, IF: 4.757) CCF推荐 Kaiying Zhu, Xiaoyan Jiang, Zhijun Fang, Yongbin Gao, Hamido Fujita, and Jenq-Neng Hwang. "Photometric transfer for direct visual odometry." Knowledge-Based Systems (2021): 106671. (SCI, Impact Factor: 8.139) 2区 Yi Wu and Xiaoyan Jiang* and Zhijun Fang and Yongbin Gao and Hamido Fujita. Multi-modal 3D Object Detection by 2D-guided Precision Anchor Proposal and Multi-layer Fusion. Applied Soft Computing. 2021. (SCI, IF: 8.263) 2区 Jingming Zhao, Juan Zhang, Zhi Li, Jenq-Neng Hwang, Yongbin Gao, and Zhijun Fang, “DD-CycleGAN: Unpaired image dehazing via Double-Discriminator Cycle-Consistent Generative Adversarial network,” Engineering Applications of Artificial Intelligence (EAAI), vol. 82, pp. 263-271, 2019. (SCI, IF: 7.802) 2区 Junxin Lu, Zhijun Fang, Yongbin Gao, Jieyu Chen, “Line-based Visual Odometry using Local Gradient Fitting,” Journal of Visual Communication and Image Representation, 2021. (SCI, IF: 2.887) CCF推荐 Yuji Zhuang, Xiaoyan Jiang, Yongbin Gao, Zhijun Fang, Hamido Fujuta, “Unsupervised Monocular Visual Odometry for Fast-Moving Scenes Based on Optical Flow Network with Feature Point Matching Constraint,” accepted, Sensors, 2023. Jiuqing Dong, Yongbin Gao*, Hyo Jong Lee, Heng Zhou, Yifan Yao, Zhijun Fang, Bo Huang, “Action Recognition Based on the Fusion of Graph Convolutional Networks with High Order Features,” Applied Sciences, vol. 10, no. 4, 2020. (SCI, IF: 2.838) Yongbin Gao, Hyo Jong Lee, “Local Tiled Deep Networks for Recognition of Vehicle Make and Model,” vol. 16, no. 2, pp. 1-13, Feb. 2016, Sensors. (SCI, IF: 3.857) Jia Gu, Zhijun Fang, Yongbin Gao, Fangzeng Tian, Segmentation of coronary arteries images using global feature embedded network with active contour loss, Computerized Medical Imaging and Graphics 86, 101799, 2020. (SCI, IF: 3.750) Lingyu Ji, Xiaoyan Jiang*, Yongbin Gao*, Zhijun Fang, Qinping Cai, Ziran Wei, ADR‐Net: Context extraction network based on M‐Net for medical image segmentation, Medical Physics 47 (9), 4254-4264, 2020. (SCI, IF: 4.506) Bo Huang, Ziran Wei, Xianhua Tang, Hamido Fujita, Qingping Cai, Yongbin Gao, Tao Wu, Liang Zhou, “Deep learning network for medical volume data segmentation based on multi axial plane fusion,” Computer Methods and Programs in Biomedicine, 2021. (SCI, IF: 7.027)2区
|
|
|