Gang Li Professor

• Department: School of energy and electrical engineering
• Gender: male
• BirthDate:
• Career: Professor
• Degree: Doctor
• Academic Credentials: Doctor degree
• Graduate School: Chang an University
• Tel: 15229296166
• Email: 15229296166@chd.edu.cn
• Address School: Chang an University
• PostCode School: 710064
• Fax School:
• Office Location: Chang an University
• Education experience:

近年发表的智慧交通、机器视觉和新能源融合领域的学术论文如下：

[1] Shanchuan Yu, Yi Li, Zhaoze Xuan, Yishun Li, and Gang Li*，Real-Time Risk Assessment for Road Transportation of Hazardous Materials Based on GRU-DNN with Multimodal Feature Embedding[J]. Applied Sciences,2022,12(21):11130; https://doi.org/10.3390/app122111130

[2] Gang Li, Zhongyuan Fang, AL MAHBASHI, MOHAMMED, Tong Liu, Zhihao Deng, Automated bridge crack detection based on improving encoder-decoder network and stripe pooling[J]. Journal of Infrastructure Systems, 2022, Accepted.

[3] Gang Li*, Tong Liu, Zhongyuan Fang, Qian Shen, Jawad Ali, Automatic bridge crack detection using boundary refinement based on real-time segmentation network[J]. Structural Control and Health Monitoring，2022:e2991.https://doi.org/10.1002/stc.2991

[4] QiHong Li, LingJia Liu, YongJun Zhou, Gang Li*, and Yu Zhao, Robust, accurate, and improved measurement of structural deformation based on off-axis digital image correlation[J].Applied Optics, 2022,61(1):1616-1623

[5] Xuan Zheng, Shuailong Zhang, Xue Li, Gang Li*, Lightweight Bridge Crack Detection Method Based on SegNet and Bottleneck Depth-Separable Convolution with Residuals[J]. IEEE Access, 2021,9(12):161649-161668

[6] 谢耀华，代玉，周欣，李刚*，基于双向特征金字塔和残差网络的危化品运输车辆检测，2022,31(1):218-225

[7] 李刚，陈永强，何廷全等，改进的多分支特征共享结构网络在路面裂缝检测中的应用[J].激光与光电子学进展，2022，59(12):1215005

[8] Gang Li, Yongqiang Chen, Jian Zhou, et al. Road crack detection and quantification based on segmentation network using architecture of matrix[J]. Engineering Computations, 2021,6:

[9] Gang Li, Dongchao Lan, et al. Automatic pavement crack detection based on single stage salient-instance segmentation and concatenated feature pyramid network[J]. International Journal of Pavement Engineering, 2021,6:

[10] Gang Li, Xiyuan Li, Jian Zhou, et al. Pixel-level bridge crack detection using a deep fusion about recurrent residual convolution and context encoder network[J]. Measurement, 2021,176(5):109171.

[11] Wenting Qiao, Qiangwei Liu, Xiaoguang Wu, Biao Ma, Gang Li*. Automatic Pixel-Level Pavement Crack Recognition Using a Deep Feature Aggregation Segmentation Network with a scSE Attention Mechanism Module[J]. Sensors, 2021,21(9), 2902. 通讯作者

[12] Wenting Qiao, Biao Ma, Qiangwei Liu, Xiaoguang Wu, Gang Li*. Computer Vision-based Bridge Damage Detection using Deep Convolutional Networks with Expectation Maximum Attention Module[J]. Sensors, 2021, 21(3), 824. 通讯作者

[13] Gang Li, Qiangwei Liu, Wei Ren, et al. Automatic recognition and analysis system of asphalt pavement cracks using interleaved low-rank group convolution hybrid deep network and SegNet fusing dense condition random field[J]. Measurement, 2021,170(1):108693

[14] Gang Li, Xueli Ren, Wenting Qiao, et al.Automatic bridge crack identification from concrete surface using ResNeXt with postprocessing[J]. Structural Control and Health Monitoring, 2020,27(11):1-20. SCI检索

[15] Gang Li, Jian Wan, Shuanhai He, et al. Semi-Supervised Semantic Segmentation Using Adversarial Learning for Pavement Crack Detection[J]. IEEE Access,2020, 8(3):51446-51459.

[16] Gang Li, Biao Ma, Shuanhai He, et al.Automatic Tunnel Crack Detection Based on U-Net and a Convolutional Neural Network with Alternately Updated Clique[J]. Sensors,2020,20(3):1-23.

[17] Gang Li, Qiangwei Liu, et al. Automatic crack recognition for concrete bridges by fully convolutional neural network and Naive Bayes data fusion based on visual detection system[J]. Measurement Science and Technology, 2020, 27(4):1-17. SCI二区检索：000532330500001

[18] Gang Li, Chao Wang, Depeng Han, et al.Deep Principal Correlated Auto-Encoders with Application to Imaging and Genomics Data Integration[J]. IEEE Access, 2020,8(1):20093 – 20107.

[19] Gang Li, Depeng Han, Chao Wang, et al. Application of deep canonically correlated sparse autoencoder for the classification of schizophrenia[J]. Computer Methods and Programs in Biomedicine, 2020, 183(1): 1-9.SCI一区检索：000498062700005

[20] 李刚，高振阳等，改进的全局卷积网络在路面裂缝检测中的应用研究[J].激光与光电子学进展，2020，57（8）:081011

[21] 李刚，刘强伟等，复杂背景下交错低秩组卷积混合深度网络的路面裂缝检测算法研究[J]，激光与光电子学进展，2020，57(14):141031-141038

[22] 李刚，张宇博等，改进的卷积网络目标跟踪算法[J]. 计算机应用研究，2020，37（7）:2206-2210

[23] 李刚，韩德鹏，刘强伟等，基于典型相关稀疏自编码器的精神分裂症分类研究[J]. 中国医学物理学杂志，2020,3(3):391-396.

[24] 李刚，王超，韩德鹏等，基于深度主成分相关自编码器的多模态影像遗传数据研究[J]. 计算机科学，2020,4(4):60-66.

[25] Gang Li, Xiaoxing Zhao, Kai Du, et al. Recognition and evaluation of bridge cracks with modified active contour model and greedy search-based support vector machine[J]. Automation in Construction, 2017, 78(6):51-61.（SCI一区检索：000397353900005）

[26] Gang Li, Shuanhai He, Yongfeng Ju, et al. Long-distance precision inspection method for bridge cracks with image processing[J]. Automation in Construction,2014,41(5):89-95.（SCI一区检索：000334139500010）

[27] 李刚，贺拴海，巨永锋等，远距离混凝土桥梁结构表面裂缝精确提取算法[J].中国公路学报，2013,4(7)：1-8.（EI检索:20133516679465）

[28] 李刚，贺拴海，杜凯等. 桥梁下部结构裂缝提取的改进C-V模型算法[J]. 交通运输工程学报，2012，12(4)：9-16.（EI检索:20124315604048）

[29] Li Gang, He ShuanHai, Ju YongFeng, et al.. Image-Based Method for Concrete Bridge Crack Detection[J].Journal of Information & Computational Science,2013,10(8):2229-2236.（EI检索:2013251642907）

[30] Li Gang,Ju Yongfeng.Novel Approach to Pavement Cracking Detection Based on Morphology and Mutual Information[C], The 2010 Chinese Control and Decision Conference. Xuzhou,China,2010: 3219-3223.(EI检索:20103213139942)

[31] Gang Li.Improved Pavement Distress Detection Based on Contourlet Transform and Multi-direction Morphological Structuring Elements[C].Advanced Materials Research,2012,466-467:371-375,(EI检索:20121114858887)

[32] 李刚，贺昱曜，不均匀光照的路面裂缝识别和分类新方法[J].光子学报，2010，39 (8): 1405-1408

[33] 李刚，贺昱曜，赵妍，一种改进的多方位结构元素形态学和互信息量的图像分割算法[J].工程图学学报，2010，31(3):104-108

[34] 李刚，贺昱曜，多方位结构元素路面裂缝图像边缘识别算法[J].计算机工程与应用，2010，46(1)：224-226

[35] 李刚，贺昱曜，赵妍，基于大津法和互信息量的路面破损图像自动识别算法[J].微电子学与计算机，2009，26(7)：241-243

[36] 李刚，贺昱曜，赵妍，桥梁水下结构缺陷的图像分割与特征提取算法[J].计算机应用与软件，2010，27(4)：80-82

[37] Li Gang, He ShuanHai, Ju YongFeng, Concrete Cracks Recognition Based on C-V Model and Mutual Information[J]. International Journal of Advancements in Computing Technology,2012,5(6): 415-423