Loading [MathJax]/extensions/MathZoom.js

Lin Cao - IEEE Xplore Author Profile

IEEE.org
IEEE Xplore
IEEE SA
IEEE Spectrum
More Sites

- Donate
- Personal Sign In

Institutional Sign In

Institutional Sign In

ADVANCED SEARCH

Author details

Lin Cao

Publications

6

Citations

17

Publications by Year

20202024

Co-Authors:

Maoyong CaoXu ChaiJie ChenZhigang GaiHao Gao

Show All Co-Authors (24)

Lin Cao

Affiliation

Institute of Oceanographic Instrumentation

Qilu Universit of Technology (Shandong Academy of Sciences)

Qingdao, China

Publication Topics

Convolutional Neural Network,
Attention Mechanism,
Deep Features,
Deep Learning,
Feature Maps,
Shallow Features,
Texture Features,
Anchor Boxes,
Aquaculture Water,
Artificial Neural Network,
Autonomous Underwater Vehicles,
Average Precision

Biography

Lin Cao received the M.S. degree from Nankai University, Tianjin, China, in 2014. She currently works with the Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences). Her research interests include digital image processing, machine vision, computational intelligence, and deep neural networks.(Based on document published on 3 August 2020).

Publications

6

Citations

17

Publications by Year

20202024

Co-Authors:

Maoyong Cao
Xu Chai
Jie Chen
Zhigang Gai
Hao Gao

Show All Co-Authors (24)

Author's Published Works

Search History

Showing 1-6 of 6 results

Conferences (4)

Journals (2)

Sort

Filter Results

Show

Open Access Only

Range
Single Year
Lin Cao(6)
Hui Li(3)
Hailin Liu(3)
Jie Chen(3)
Xuejun Xiong(2)
Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao, China(4)
College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, China(2)
National Engineering and Technological Research Center of Marine Monitoring Equipment, Qingdao, China(2)
First Institute of Oceanography, Ministry of Natural Resources, Qingdao, China(2)
Shandong Provincial Key Laboratory of Ocean Environmental Monitoring Technology, Qingdao, China(1)
2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)(2)
IEEE Access(2)
2020 IEEE 20th International Conference on Communication Technology (ICCT)(1)
2024 7th International Conference on Computer Information Science and Application Technology (CISAT)(1)
IEEE(6)
Dalian, China(2)
Hangzhou, China(1)
Nanning, China(1)
Convolutional Neural Network(3)
Attention Mechanism(2)
Deep Features(2)
Deep Learning(2)
Feature Maps(2)

Select All on Page

Sort By

Results

Study on dynamic compensation of marine conductivity sensor based on Particle Swarm Optimization Algorithm

Kaili Hu;Xu Chai;Lin Cao;Fengxiang Guo;Xueyu Zhang;Guangsen Xia;Xuesong Zhou;Mei Zhang;Lili Zhang;Shousheng Liu;Zhigang Gai

2024 7th International Conference on Computer Information Science and Application Technology (CISAT)

Year: 2024 | Conference Paper |

HTML

Aiming at the problem of insufficient response speed of the marine conductivity sensor, a method of designing a dynamic compensation filter model for dynamic compensation is proposed to improve the response speed of the sensor. The dynamic response curve of the sensor was measured by the marine sensor time constant measurement device, and the dynamic compensation filter model of the conductivity s...Show More

Study on dynamic compensation of marine conductivity sensor based on Particle Swarm Optimization Algorithm

Kaili Hu;Xu Chai;Lin Cao;Fengxiang Guo;Xueyu Zhang;Guangsen Xia;Xuesong Zhou;Mei Zhang;Lili Zhang;Shousheng Liu;Zhigang Gai

2024 7th International Conference on Computer Information Science and Application Technology (CISAT)

Year: 2024 | Conference Paper |

Pixel-Level Prediction for Ocean Remote Sensing Image Features Fusion Based on Global and Local Semantic Relations

Hao Gao;Xuejun Xiong;Lin Cao;Dingfeng Yu;Guangbing Yang;Lei Yang

Year: 2021 | Volume: 9 | Journal Article |

Cited by: Papers (3)

HTML

With the rapid development of remote-sensing imaging technology, remote-sensing images have become increasingly diverse, and people are paying more attention to ocean remote-sensing research. Because ocean remote-sensing data are complex, and the ocean environment is diverse, results will differ, even if the same target is detected at different times in the same scene. To obtain more semantic feat...Show More

Pixel-Level Prediction for Ocean Remote Sensing Image Features Fusion Based on Global and Local Semantic Relations

Hao Gao;Xuejun Xiong;Lin Cao;Dingfeng Yu;Guangbing Yang;Lei Yang

Year: 2021 | Volume: 9 | Journal Article |

Incremental Learning of Infrared Vehicle Detection Method Based on SSD

Hui Li;Jian Yuan;Hailin Liu;Lin Cao;Jie Chen;Zhaowen Zhang

2020 IEEE 20th International Conference on Communication Technology (ICCT)

Year: 2020 | Conference Paper |

Cited by: Papers (4)

HTML

An incremental Learning of infrared vehicle detection method based on SSD(Single Shot MultiBox Detector) was proposed to solve the problems such as lack of detail in infrared vehicle images, difficulty in extracting feature information and low detection accuracy. Through incremental learning and training, the CNN detection model based on SSD was fine-tuning, and the Pascal VOC data set was pre-tra...Show More

Incremental Learning of Infrared Vehicle Detection Method Based on SSD

Hui Li;Jian Yuan;Hailin Liu;Lin Cao;Jie Chen;Zhaowen Zhang

2020 IEEE 20th International Conference on Communication Technology (ICCT)

Year: 2020 | Conference Paper |

Research on Matching Method of Ocean Observation Data Based on DC-WKNN Algorithm

Jie Chen;Yifan Hu;Hailin Liu;Bin Lv;Lin Cao;Hui Li

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)

Year: 2020 | Conference Paper |

Cited by: Papers (1)

HTML

According to the characteristics of ocean observation data, such as massive, heterogeneous, multi-source, multi-class and multi-dimensional, it is difficult to classify and match ocean observation data quickly and accurately with traditional KNN for large-scale integration. A method of ocean observation data matching based on density clipping and weighted KNN (DC-WKNN) is proposed in this paper. F...Show More

Research on Matching Method of Ocean Observation Data Based on DC-WKNN Algorithm

Jie Chen;Yifan Hu;Hailin Liu;Bin Lv;Lin Cao;Hui Li

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)

Year: 2020 | Conference Paper |

Study on Prediction of Dissolved Oxygen Content in Aquaculture Water

Heqing Geng;Yifan Hu;Hailin Liu;Jie Chen;Lin Cao;Hui Li

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)

Year: 2020 | Conference Paper |

Cited by: Papers (2)

HTML

Aiming at the problems of low accuracy, slow convergence and poor robustness of traditional neural network water quality prediction method, a dissolved oxygen content prediction model based on combining algorithm of improved Fruit fly optimization algorithm and BP neural network (IFOABP) is proposed. The best combination of weights and biases parameters of BP neural network is obtained by improved...Show More

Study on Prediction of Dissolved Oxygen Content in Aquaculture Water

Heqing Geng;Yifan Hu;Hailin Liu;Jie Chen;Lin Cao;Hui Li

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)

Year: 2020 | Conference Paper |

Semantic Segmentation of Marine Remote Sensing Based on a Cross Direction Attention Mechanism

Hao Gao;Lin Cao;Dingfeng Yu;Xuejun Xiong;Maoyong Cao

Year: 2020 | Volume: 8 | Journal Article |

Cited by: Papers (7)

HTML

With the development of remote sensing technology, the semantic segmentation and recognition of various things in the ocean have become more and more frequent. Due to the wide variety of marine things and the large differences in morphology, it has brought greater difficulties to the recognition of marine remote sensing images. In order to obtain better segmentation results of ocean remote sensing...Show More

Semantic Segmentation of Marine Remote Sensing Based on a Cross Direction Attention Mechanism

Hao Gao;Lin Cao;Dingfeng Yu;Xuejun Xiong;Maoyong Cao

Year: 2020 | Volume: 8 | Journal Article |

IEEE Personal Account

Change username/password

Purchase Details

Payment Options
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

Follow

About IEEE Xplore | Contact Us | Help | Accessibility | Terms of Use | Nondiscrimination Policy | IEEE Ethics Reporting | Sitemap | IEEE Privacy Policy

A public charity, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.

© Copyright 2025 IEEE - All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies.

IEEE Account

Change Username/Password
Update Address

Purchase Details

Payment Options
Order History
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical Interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

About IEEE Xplore
Contact Us
Help
Accessibility
Terms of Use
Nondiscrimination Policy
Sitemap
Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.