个人简介
张永强,博士,讲师(师资博后), 硕士研究生导师,入选“2020全国博士后创新人才计划(博新计划)”,仪器科学与工程学院 电测技术及智能控制研究所。从事人工智能、深度学习/机器学习、计算机视觉等相关科研工作,包括底层视觉任务(图像超分辨、图像去模糊/去雨/去雾等),和一些顶层视觉任务(如物体检测、图像分割等),已发表SCI/EI学术论文20余篇,其中包括多篇国际顶级期刊文章(TNNLS,PR,IJCV等)和多篇人工智能/计算机视觉顶级国际会议文章(CVPR/ICCV/ECCV/Nips/AAAI),发明专利授权11项。主持中国博士后基金创新人才支持计划项目、国家青年自然科学基金、黑龙江省博士后面上资助、黑龙江省自然科学基金联合引导项目、以及多项航空航天项目等研究工作。担任T-PAMI、TNNLS、PR、PRL、SPL等多个期刊,以及CVPR/ICCV/ECCV/AAAI等多个国际会议审稿人。
工作经历
2021.5-今 哈尔滨工业大学 仪器科学与工程学院,硕士研究生导师
2020.9-今 哈尔滨工业大学 仪器科学与工程学院,师资博后/讲师
2020.9-今 哈尔滨工业大学 仪器科学与工程学院 1901004班,班主任
2020.7-今 哈尔滨工业大学 计算机科学与技术学院,博士后
教育经历
2015.9-2020.4 哈尔滨工业大学 仪器科学与工程学院,博士
2013.9-2015.7 哈尔滨工业大学 电气工程及自动化学院,硕士
2009.9-2013.7 哈尔滨理工大学 测控技术与通信工程学院,学士
2017.3-2018.4 King Abdullah University of Science & Technology,Visual Computing Center, Visiting Ph.D. Student
重要荣誉奖励
2023年 获“黑龙江省人工智能学会优秀博士学位论文”一等奖
2023年 获“第十一届全国大学生光电竞赛”优秀指导教师奖
2022年 获“第十届全国大学生光电竞赛”优秀指导教师奖
2022年 获“国家自然科学基金-青年科学基金项目”资助
2021年 获“第九届全国大学生光电竞赛”优秀指导教师奖
2020年 入选“全国博士后创新人才支持计划(博新计划)”
近期论文
查看导师新发文章
(温馨提示:请注意重名现象,建议点开原文通过作者单位确认)
Yongqiang Zhang#, Yin Zhang#, Rui Tian, Zian Zhang, Yancheng Bai, Wangmeng Zuo, Mingli Ding, “ThumbDet: One thumbnail image is enough for object detection", Pattern Recognition, accept, 2023.(SCI,Q1/中科院一区,IF=8.0)
Na Dong, Yongqiang Zhang*, Mingli Ding, Yancheng Bai, “Class-incremental object detection", Pattern Recognition, accept, 2023.(SCI,Q1/中科院一区,IF=8.0)
Yueyi Zhu, Yongqiang Zhang*, Mingli Ding*, Wangmeng Zuo, “Uncertainty-aware Graph-guided Weakly Supervised Object Detection", IEEE Transactions on Circuits and Systems for Video Technology, accept, 2023.(SCI,Q1/中科院一区, IF=8.4)
Na Dong, Yongqiang Zhang, Mingli Ding, Gim Hee Lee, "Boosting Long-tailed Object Detection via Step-wise Learning on Smooth-tail Data", International Conference on Computer Vision 2023, ICCV2023, Paris, France. (Poster) (CCF A类)
Na Dong, Yongqiang Zhang, Mingli Ding, Gim Hee Lee, “Incremental-detr: Incremental few-shot object detection via self-supervised learning", Association for the Advancement of Artificial Intelligence 2023, AAAI2023, 37(1): pp.543-551, Washington DC, USA. (Poster) (CCF A类)
Na Dong, Yongqiang Zhang*, Mingli Ding, Shibiao Xu, Yancheng Bai, “One-stage object detection knowledge distillation via adversarial learning”, Applied Intelligence, 2022, 52(4): 4582-4598. (SCI,Q2/中科院二区,IF=5.3)
Guanglei Yang, Mingli Ding, Yongqiang Zhang, "Bi-directional class-wise adversaries for unsupervised domain adaptation", Applied Intelligence, 2022, 52(4): 3623-3639. (SCI,Q2/中科院二区, IF=5.3)
Na Dong, Yongqiang Zhang, Mingli Ding, Gim Hee Lee, "Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detection", Advances in Neural Information Processing Systems 2021, NIPS2021, 34: pp.30492-30503.}, New Orleans, USA. (Poster) (CCF A类)
Cong Wang, Mingli Ding*, Yongqiang Zhang*, Lina Wang, “A Single Image Enhancement Technique Using Dark Channel Prior”, Applied Sciences,11(6): 2712,2021.(SCI, Q2/中科院三区, IF=2.838)
Yongqiang Zhang, Mingli Ding, Yancheng Bai, Bernard Ghanem, “KGSNet: Key-point Guided Super-resolution Network for Pedestrian Detection in the Wild”, IEEE Transactions on Neural Networks and Learning Systems,32(5):2251-2265,2020.(SCI, Q1/中科院一区, IF=8.793)
Yongqiang Zhang, Yancheng Bai, Mingli Ding, Bernard Ghanem, “Multi-Task Generative Adversarial Network for Detecting Small Objects in the Wild”, International Journal of Computer Vision, vol. 128(6), pp. 1810-1828, 2020.(SCI, Q1/中科院二区, IF=5.698)
Yongqiang Zhang, Mingli Ding, Yancheng Bai, Bernard Ghanem, “Beyond Weakly-supervised: Pseudo Ground Truths Mining for Missing Bounding-boxes Object Detection”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 30(4), pp. 983-997, 2020.(SCI,Q1/中科院二区, IF=4.133)
Yongqiang Zhang, Mingli Ding, Yancheng Bai, Bernard Ghanem, “Detecting Tiny Faces in the Wild Based on Generative Adversarial Network and Contextual Information”, Pattern Recognition, vol. 94, pp. 74-86, 2019.(SCI, Q1/中科院一区, IF=7.196)
Yongqiang Zhang, Mingli Ding, Yancheng Bai, Bernard Ghanem, “Learning a strong detector for action localization in videos”, Pattern Recognition Letters, vol. 128, pp. 407-413, 2019.(SCI,Q2/中科院三区, IF=3.255)
Yongqiang Zhang, Yancheng Bai, Mingli Ding, Yongqiang Li, Bernard Ghanem, “Weakly-supervised Object Detection via Mining Pseudo Ground Truth Bounding-boxes”, Pattern Recognition, vol. 84, pp. 68–81, 2018.(SCI, Q1/中科院一区, IF=7.196)
Yongqiang Zhang, Yancheng Bai, Mingli Ding, Yongqiang Li, Bernard Ghanem, “W2F: A WeaklySupervised to Fully-Supervised Framework for Object Detection”, Computer Vision and Pattern Recognition 2018, CVPR2018, pp. 928–936, Salt Lake City, USA. (Poster)(CCF A 类,计算机视觉/人工智能领域三大顶会之一,录取率 21%)
Yancheng Bai*, Yongqiang Zhang*, Mingli Ding, Bernard Ghanem, “SOD-MTGAN: Small Object Detection via Multi-Task Generative Adversarial Network”, European conference on computer vision 2018, ECCV2018, pp. 206-221, Munich, Germany. (* Co-first author) (Poster)(CCF A 类,计算机视觉/人工智能领域三大顶会之一,录取率 23%)
Yancheng Bai, Yongqiang Zhang, Mingli Ding, Bernard Ghanem, “Finding Tiny Faces in the Wild with Generative Adversarial Network”, Computer Vision and Pattern Recognition 2018, CVPR2018, pp. 21-30, Salt Lake City, USA. (Oral)(CCF A 类,计算机视觉/人工智能领域三大顶会之一,录取率 7%)