杨汉铎【博士】

发布者:轨道交通学院管理员发布时间:2025-11-21浏览次数:44

杨汉铎,男,19977月,安徽亳州人,中共党员,博士学历。共发表论文 13 篇,其中以第一作者和通讯作者发表论文 5 篇,担任 Automation In ConstructionIEEE Transactions on CyberneticsJournal of Big Data Measurement 等多个学术期刊审稿人。

个人经历

2013.09 - 2017.06    土木工程,东北林业大学,学 士

2018.09 - 2021.06    交通运输工程,浙江大学,硕 士

2021.09 – 2025.06    交通运输,东南大学, 博 士

2025.06 – 至今          轨道交通学院,安徽职业技术大学,专任教师

研究方向

基础设施智能监测与决策、机器/深度学习与大数据分析技术、基础设施智能体应用

代表性成果

[1] ZHANG E H, MA T, YANG H D, et al. Milepost-to-Vehicle Monocular Depth Estimation with Boundary Calibration and Geometric Optimization [J]. Electronics, 2025, 14(17).

[2] YANG H, MA T, TONG Z, et al. Deployment strategies for lightweight pavement defect detection using deep learning and inverse perspective mapping [J]. Automation in Construction, 2024, 167: 105682.

[3] HAN C, YANG H*, YANG Y. Enhancing pixel-level crack segmentation with visual mamba and convolutional networks [J]. Automation in Construction, 2024, 168: 105770.

[4] YANG H, HUYAN J, MA T, et al. A Novel Applicable Shadow Resistant Neural Network Model for High-Efficiency Grid-Level Pavement Crack Detection [J]. IEEE Transactions on Artificial Intelligence, 2024, 5(9): 4535-49.

[5] HAN C, YANG H, MA T, et al. CrackDiffusion: A two-stage semantic segmentation framework for pavement crack combining unsupervised and supervised processes [J]. Automation in Construction, 2024, 160: 105332.

[6] YANG H, MA T, HUYAN J, et al. Aggregation segregation generative adversarial network (AG-GAN) facilitated multi-scale segregation detection in asphalt pavement paving stage [J]. Engineering Applications of Artificial Intelligence, 2024, 129: 107663.

[7] PENG Y, YANG H, et al. Aggregate boundary recognition of asphalt mixture CT images based on convolutional neural networks [J]. 2024, 25(5): 1127-43.

[8] YANG H, HUYAN J, MA T, et al. Novel Computer Tomography image enhancement deep neural networks for asphalt mixtures [J]. Construction and Building Materials, 2022, 352: 129067.

[9] 彭勇,杨汉铎,陆学元,.基于离散元法的空隙特征对沥青混合料虚拟剪切疲劳寿命的影响[J].吉林大学学报(工学版),2021,51(03):956-964.

[9]一种基于深度学习的沥青混合料中集料边界识别与划分方法(授权发明专利 编号CN202110879775.0)

[10]一种沥青混合料模型随机空隙生成方法(授权发明专利 编号CN202011203878.7)

[11]一种随机生成多结构层沥青路面离散元模型的方法(授权发明专利 编号CN201911418035.6)