CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 12342 > Article
Paper
12 October 2022 Dock detection method in remote sensing images based on improved YOLOv4
Haitao Guo, Hui Gao, Chao Guo, Jun Lu, Yuzhun Lin
Author Affiliations +
Proceedings Volume 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022); 123420E (2022) https://doi.org/10.1117/12.2643035
Event: Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 2022, Wuhan, China
Abstract
The dock target in remote sensing images has the characteristics of slender structure and direction arbitrarily. The general target detection algorithm based on the convolutional neural network cannot effectively obtain the direction information of the target, which cannot meet the actual demand of dock detection. This study designed a deep convolutional neural network architecture in any direction based on the YOLOv4 algorithm aimed at resolving the above problems. First, the multidimensional coordinate method was used to calibrate the dock target so that the network could contain the direction information of the target. Second, the loss function of the algorithm was optimized to make it suitable for directional target detection. Finally, an attention mechanism was introduced to enhance the extraction ability of the algorithm and further improve its detection accuracy. Two datasets of dock target detection from remote sensing images were selected for experiments, and the results showed that the improved YOLOv4 network was better than the other networks in the dock target detection task.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Haitao Guo, Hui Gao, Chao Guo, Jun Lu, and Yuzhun Lin "Dock detection method in remote sensing images based on improved YOLOv4", Proc. SPIE 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 123420E (12 October 2022); https://doi.org/10.1117/12.2643035
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 8 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Target detection
Detection and tracking algorithms
Remote sensing
Feature extraction
Convolution
Convolutional neural networks
Environmental sensing
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top