Self-Correction Ship Tracking and Counting with Variable Time Window Based on YOLOv3
Automatic ship detection, recognition, and counting are crucial for intelligent maritime surveillance, timely ocean rescue, and computer-aided decision-making. YOLOv3 pretraining model is used for model training with sample images for ship detection. The ship detection model is built by adjusting an...
Saved in:
Main Authors: | Chun Liu, Jian Li |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2021/2889115 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Ship Target Detection Algorithm Based on Improved YOLOv3 for Maritime Image
by: Dehai Chen, et al.
Published: (2021-01-01) -
Retracted: IOT Monitoring System for Ship Operation Management Based on YOLOv3 Algorithm
by: Journal of Control Science and Engineering
Published: (2023-01-01) -
Vehicle Detection and Tracking Based on Improved YOLOv8
by: Yunxiang Liu, et al.
Published: (2025-01-01) -
An Optimization Model for Tramp Ship Scheduling considering Time Window and Seaport Operation Delay Factors
by: Ang Yang, et al.
Published: (2021-01-01) -
High-Accuracy Real-Time Fish Detection Based on Self-Build Dataset and RIRD-YOLOv3
by: Wenkai Wang, et al.
Published: (2021-01-01)