Autonomous detection of damage to multiple steel surfaces from 360° panoramas using deep neural networks-Reference-Cited by-同舟云学术

Autonomous detection of damage to multiple steel surfaces from 360° panoramas using deep neural networks

Author:

Luo Cai¹,Yu Leijian²,Yan Jiaxing³⁴,Li Zhongwei¹,Ren Peng¹,Bai Xiao⁵,Yang Erfu²,Liu Yonghong⁶

Affiliation:

1. College of Oceanography and Space Informatics China University of Petroleum (East China) Qingdao China

2. Department of Design, Manufacturing & Engineering Management University of Strathclyde Glasgow UK

3. School of Mechanical Engineering Xi'an Jiaotong University Shaanxi China

4. State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Shaanxi China

5. School of Computer Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing China

6. College of Mechanical and Electronic Engineering China University of Petroleum (East China) Qingdao China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Science Applications,Civil and Structural Engineering

Link

Reference55 articles.

Cited by 53 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献