个人简介
【个人简介】
贾伟，博士，合肥工业大学计算机与信息学院教授，博士生导师。中国图象图形学学会青年工作委员会秘书长。中国自动化学会模式识别与机器智能专业委员会常务委员。中国人工智能学会模式识别专业委员会委员。中国人工智能学会智能交互专业委员会委员。中国计算机学会计算机视觉专业委员会委员。中国图象图形学会机器视觉专业委员会委员。1998年于华中师范大学信息管理系获理学学士学位，2004年于合肥工业大学计算机学院获得工学硕士学位，2008年于中国科技大学自动化系获工学博士学位，获“2008年度中科院院长优秀奖”等奖励。担任IEEE TPAMI、TIP、TNNLS、TAC、TIFS、TCYB、TMM、TCSVT、TIM、PR、CVPR、IJCAI、AAAI、ICPR等多个国际顶级期刊审稿人和国际顶级会议程序委员会委员及领域主席。首届中科院青年创新促进会会员。视觉与学习青年研讨会（VALSE）第一届在线理事会副主席、在线委员会副主席，VALSE常务委员。2015中国生物特征识别青年论坛指导委员会委员。2016/2017/2018/2019/2021/2022中国生物特征识别会议宣传主席。2017年中国计算机视觉大会宣传主席。VALSE 2018/2020/2021/2022宣传主席，VALSE 2019程序委员会主席。中国图象图形学学会2019暑期联合会议组织委员会主席。中国模式识别与计算机视觉大会2020（PRCV 2020）竞赛主席。中国模式识别与计算机视觉大会2022/2023（PRCV 2022, 2023）宣传主席。中国图象图形学学会2020年青年科学家论坛程序委员会主席，中国图象图形学学会2021年青年科学家会议程序委员会主席。国际生物特征识别领域顶级会议IJCB 2021 宣传主席。国际图像与图形大会2023（ICIG 2023）社交媒体主席。“新一代人工智能”西部地区论坛执行主席。国家自然科学基金函评专家。已获得4项国家自然科学基金的资助。已经发表SCI论文近百篇，其中在IEEE Transactions 会刊等国际顶级及权威期刊上发表论文CCF A类及中科院1区论文40多篇，论文被引近5000余次，H因子32。获得授权发明专利7项。担任《中国图象图形学学报》编委。主要研究兴趣为人工智能、生物特征识别、计算机视觉、模式识别等。
【招生信息】
招收计算机、人工智能等专业的博士研究生和硕士研究生。
实验室氛围和谐进取，研究方向前景好，欢迎认真热情、脚踏实地的学生报考。
优秀的研究生可以推荐到985高校进行联合培养，也可以推荐到知名人工智能企业进行实习。
【研究方向】
主要研究方向：人工智能、计算机视觉、图像处理、模式识别、生物特征识别
具体研究方向一：人工智能基础理论
深度学习
具体研究方向二：生物特征识别
掌纹识别、静脉识别、手部生物特征识别、儿童生物特征识别、生物特征识别基本理论
具体研究方向三：智能交通
车牌识别、车型识别、视频结构化
具体研究方向四：视频分析
2D/3D人体姿态估计、动作识别
【主持及负责的科研项目】
[1]. 安徽省重点研发项目，编号:202004d07020008, “基于高效深度卷积神经网络的摩托车违法驾驶抓拍系统”，30万元，2020.1-2022.12 （主持）
[2]. 国家自然科学基金面上项目，编号:62076086,“基于非接触式多种手部模态融合识别的大规模人群身份认证关键问题研究”，58万元，2021.1-2024.12 （主持）
[3]. 安徽省重点研发项目，“面向智能交互的高密度压力阵列足部信息获取与分析系统”，60万，2018-2020（项目合作单位负责人）
[4]. 中央高校基本业务费项目，“新一代生物特征识别体系结构研究”，30万元，2018-2019（主持）
[5]. 国家自然科学基金面上项目，编号:61673157,“面向移动身份认证的中低分辨率掌纹识别关键问题研究”，60万元，2017.1-2020.12 （主持）
[6]. 国家自然科学基金面上项目，编号:61175022，“基于人脸和人手信息融合的面向成人和儿童的非接触式身份鉴别方法研究”，63万元，2012.1-2015.12 （主持）
[7]. 国家自然科学基金青年基金项目, 编号:60705007 ，“基于脚纹识别的婴幼儿身份认证关键技术研究”，20万元，2008.1-2010.12（主持）
[8]. 合肥物质科学中心方向性培育项目,“面向民用核设施的民众风险沟通研究”40万元，2014.9-2016.9（联合负责人）
[9]. 中科院十二五信息化数据库重点项目，“领域基础科学数据整合与集成应用项目”，140万元，2013.7-2015.12（执行负责人）
[10]. 中科院青年创新促进会成员专项基金，40万元，2011.9-2015.8 （主持）
[11]. 中科院院长奖启动基金项目，“掌纹的快速检索算法研究”，10万元，2009.7-2012.6（主持）
[12]. 中科院智能所知识创新工程领域前沿重点项目子课题,“基于摄像机与柔性阵列传感器的双模态步态识别”，10万元，2009.1-2011.12（主持）
[13]. 中科院合肥物质科学研究院知识创新工程青年人才项目“掌纹识别关键技术研究”，12万，2010.1-2011.12 （主持）
【发表的部分期刊论文】
[1] Y. Yu, H. Liu, Y. Fu, W. Jia, J. Yu and Z. Yan, Embedding Pose Information for Multiview Vehicle Model Recognition, IEEE Transactions on Circuits and Systems for Video Technology, 2022.
[2] Y. Zhao, W. Jia, and R. Wang, “Rethinking deinterlacing for early interlaced videos,” IEEE Transactions on Circuits and Systems for Video Technology, 2022.
[3] Y. Chen, Y. Zhao, L. Cao, W. Jia, and X. Liu, “Learning Deep Blind Quality Assessment for Cartoon Images,” IEEE Transactions on Neural Networks and Learning Systems, 2022.
[4] Y. Zhao, R. Wang, Y. Chen, W. Jia*, X. Liu, and W. Gao, “Lighter but efficient bit-depth expansion network,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 31, no. 5, pp. 2063-2069, 2021.
[5] L. Zhang, Q. Duan, D. Zhang, W. Jia, and X. Wang, “AdvKin: Adversarial convolutional network for kinship verification,” IEEE transactions on cybernetics, vol. 51, no. 12, pp. 5883 - 5896, 2021.
[6] Y. Yu, H. Li, J. Wang, H. Min, W. Jia*, J. Yu, and C. Chen, “A Multilayer Pyramid Network Based on Learning for Vehicle Logo Recognition,” IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 5, pp. 3123-3134, 2021.
[7] L. Fei, B. Zhang, L. Zhang, W. Jia, J. Wen, and J. Wu, “Learning compact multifeature codes for palmprint recognition from a single training image per palm,” IEEE Transactions on Multimedia, vol. 23, pp. 2930 - 2942, 2021.
[8] L. Fei, B. Zhang, S. Teng, Z. Guo, S. Li, and W. Jia, “Joint multiview feature learning for hand-print recognition,” IEEE Transactions on Instrumentation and Measurement, vol. 69, no. 12, pp. 9743-9755, 2020.
[9] L. Fei, B. Zhang, W. Jia, J. Wen, and D. Zhang, “Feature extraction for 3-D palmprint recognition: A survey,” IEEE Transactions on Instrumentation and Measurement, vol. 69, no. 3, pp. 645-656, 2020.
[10] M. Cao, L. Zheng, W. Jia, H. Lu, and X. Liu, “Accurate 3-D reconstruction under IoT environments and its applications to augmented reality,” IEEE Transactions on Industrial Informatics, vol. 17, no. 3, pp. 2090-2100, 2021.
[11] M. Cao, L. Zheng, W. Jia, and X. Liu, “Joint 3D reconstruction and object tracking for traffic video analysis under IoV environment,” IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 6, pp. 3577 - 3591, 2021.
[12] Y. Zhao, R. Wang, W. Jia*, W. Zuo, X. Liu, and W. Gao, “Deep reconstruction of least significant bits for bit-depth expansion,” IEEE Transactions on Image Processing, vol. 28, no. 6, pp. 2847-2859, 2019.
[13] L. Fei, B. Zhang, Y. Xu, D. Huang, W. Jia, and J. Wen, “Local discriminant direction binary pattern for palmprint representation and recognition,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 30, no. 2, pp. 468-481, 2019.
[14] L. Fei, B. Zhang, Y. Xu, Z. Guo, J. Wen, and W. Jia, “Learning discriminant direction binary palmprint descriptor,” IEEE Transactions on Image Processing, vol. 28, no. 8, pp. 3808-3820, 2019.
[15] Y. Chen, Y. Zhao, S. Li, W. Zuo, W. Jia, and X. Liu, “Blind Quality Assessment for Cartoon Images,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 30, no. 9, pp. 3282-3288, 2019.
[16] X. Wu, W. Zuo, L. Lin, W. Jia, and D. Zhang, “F-SVM: Combination of feature transformation and SVM learning via convex relaxation,” IEEE transactions on neural networks and learning systems, vol. 29, no. 11, pp. 5185-5199, 2018.
[17] H. Min, W. Jia*, Y. Zhao, W. Zuo, H. Ling, and Y. Luo, “LATE: A level-set method based on local approximation of Taylor expansion for segmenting intensity inhomogeneous images,” IEEE Transactions on Image Processing, vol. 27, no. 10, pp. 5016-5031, 2018.
[18] W. Kang, Y. Lu, D. Li, and W. Jia, “From noise to feature: Exploiting intensity distribution as a novel soft biometric trait for finger vein recognition,” IEEE transactions on information forensics and security, vol. 14, no. 4, pp. 858-869, 2018.
[19] W. Jia, Y. Zhao, R. Wang, S. Li, H. Min, and X. Liu, “Are Recent SISR Techniques Suitable for Industrial Applications at Low Magnification?,” IEEE Transactions on Industrial Electronics, vol. 66, no. 12, pp. 9828-9836, 2018.
[20] L. Fei, G. Lu, W. Jia*, J. Wen, and D. Zhang, “Complete binary representation for 3-D palmprint recognition,” IEEE Transactions on Instrumentation and Measurement, vol. 67, no. 12, pp. 2761-2771, 2018.
[21] L. Fei, G. Lu, W. Jia, S. Teng, and D. Zhang, “Feature extraction methods for palmprint recognition: A survey and evaluation,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 49, no. 2, pp. 346-363, 2018.
[22] X. Qiu, W. Kang, S. Tian, W. Jia, and Z. Huang, “Finger vein presentation attack detection using total variation decomposition,” IEEE Transactions on Information Forensics and Security, vol. 13, no. 2, pp. 465-477, 2017.
[23] W. Jia, B. Zhang, J. Lu, Y. Zhu, Y. Zhao, W. Zuo, and H. Ling, “Palmprint recognition based on complete direction representation,” IEEE Transactions on Image Processing, vol. 26, no. 9, pp. 4483-4498, 2017.
[24] W. Jia, R.-X. Hu, Y.-K. Lei, Y. Zhao, and J. Gui, “Histogram of oriented lines for palmprint recognition,” IEEE Transactions on systems, man, and cybernetics: systems, vol. 44, no. 3, pp. 385-395, 2013.
[25] R.-X. Hu, W. Jia*, H. Ling, Y. Zhao, and J. Gui, “Angular pattern and binary angular pattern for shape retrieval,” IEEE Transactions on Image Processing, vol. 23, no. 3, pp. 1118-1127, 2013.
[26] Y. Zhao, D.-S. Huang, and W. Jia, “Completed local binary count for rotation invariant texture classification,” IEEE transactions on image processing, vol. 21, no. 10, pp. 4492-4497, 2012.
[27] R. Hu, W. Jia*, H. Ling, and D. Huang, “Multiscale distance matrix for fast plant leaf recognition,” IEEE transactions on image processing, vol. 21, no. 11, pp. 4667-4672, 2012.
[28] S.-L. Wang, Y.-H. Zhu, W. Jia, and D.-S. Huang, “Robust classification method of tumor subtype by using correlation filters,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 9, no. 2, pp. 580-591, 2011.
[29] W. Jia, W. Xia, B. Zhang, Y. Zhao, L. Fei, W. Kang, D. Huang, and G. Guo, “A survey on dorsal hand vein biometrics,” Pattern Recognition, vol. 120, pp. 108122, 2021.
[30] L. Fei, B. Zhang, Y. Xu, W. Jia, J. Wen, and J. Wu, “Precision direction and compact surface type representation for 3D palmprint identification,” Pattern Recognition, vol. 87, pp. 237-247, 2019.
[31] H. Min, W. Jia*, Y. Zhao, and Y.-T. Luo, “A polynomial piecewise constant approximation method based on dual constraint relaxation for segmenting images with intensity inhomogeneity,” Pattern Recognition, vol. 73, pp. 15-32, 2018.
[32] Y.-T. Luo, L.-Y. Zhao, B. Zhang, W. Jia*, F. Xue, J.-T. Lu, Y.-H. Zhu, and B.-Q. Xu, “Local line directional pattern for palmprint recognition,” Pattern Recognition, vol. 50, pp. 26-44, 2016.
[33] H. Min, W. Jia*, X.-F. Wang, Y. Zhao, R.-X. Hu, Y.-T. Luo, F. Xue, and J.-T. Lu, “An intensity-texture model based level set method for image segmentation,” Pattern Recognition, vol. 48, no. 4, pp. 1547-1562, 2015.
[34] R.-X. Hu, W. Jia*, Y. Zhao, and J. Gui, “Perceptually motivated morphological strategies for shape retrieval,” Pattern Recognition, vol. 45, no. 9, pp. 3222-3230, 2012.
[35] R.-X. Hu, W. Jia*, D. Zhang, J. Gui, and L.-T. Song, “Hand shape recognition based on coherent distance shape contexts,” Pattern Recognition, vol. 45, no. 9, pp. 3348-3359, 2012.
[36] J. Gui, Z. Sun, W. Jia, R. Hu, Y. Lei, and S. Ji, “Discriminant sparse neighborhood preserving embedding for face recognition,” Pattern Recognition, vol. 45, no. 8, pp. 2884-2893, 2012.
[37] W. Jia, D.-S. Huang, and D. Zhang, “Palmprint verification based on robust line orientation code,” Pattern Recognition, vol. 41, no. 5, pp. 1504-1513, 2008.
[38] D.-S. Huang, W. Jia, and D. Zhang, “Palmprint verification based on principal lines,” Pattern Recognition, vol. 41, no. 4, pp. 1316-1328, 2008.