Ship Detection from Highly Cluttered Images Using Convolutional Neural Network-Reference-Cited by-同舟云学术

Ship Detection from Highly Cluttered Images Using Convolutional Neural Network

Published:2021-06-26 Issue:1 Volume:121 Page:287-305
ISSN:0929-6212
Container-title:Wireless Personal Communications
language:en
Short-container-title:Wireless Pers Commun

Author:

Gupta Vishal^ORCID,Gupta Monish,Singla Parveen

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Science Applications

Link

https://link.springer.com/content/pdf/10.1007/s11277-021-08635-5.pdf

Reference46 articles.

1. Robert-Inacio F., A. Raybaud, E. Clement, “Multispectral target detection and tracking for seaport video surveillance”, Proceedings of Image and Vision Computing New Zealand 2007, pp.169–174.

2. Fefilatyev S., D. Goldgof, “Detection and tracking of marine vehicles in video”, International Conference on Pattern Recognition (ICPR), 2008.

3. Sullivan, R., Mikel, D., & Shah, M. (2008). Visual surveillance in maritime port facilities. Proceedings of the SPIE, 3978, 697811.

4. Lemoine, G., Schwartz-Juste, G., Kourti, N., Shepherd, I., Cesena, C., 2005. An open source framework for integration of vessel positions detected in space borne SAR imagery in operational fisheries monitoring and control. In: Proceedings of ENVISAT/ERS Symposium, vol. 572, pp. 252–258

5. Saur, G.,Estable,S.,Zielinski,K.,Knabe,S.,Teutsch,M.,Gabel,M.,2011. “Detection and classification of man-made off shore objects in terrasar-xand rapid eye imagery: selected results of the demarine-dekoproject”. In:Proceedings of IEEE-Spain OCEANS,pp.1–10.

Cited by 9 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

1. IoT-based nano wireless sensor approach for detection of ships using mixed convolutional neural network approach;Signal, Image and Video Processing;2024-08-01

2. Fine-grained ship image classification and detection based on a vision transformer and multi-grain feature vector FPN model;Geo-spatial Information Science;2024-04-16

3. Local feature matching from detector-based to detector-free: a survey;Applied Intelligence;2024-03

4. Image and AIS Data Fusion Technique for Maritime Computer Vision Applications;2024 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW);2024-01-01

5. A Multimodal Contrastive Pre-training Framework for Automatic Ship Detection in SAR Imagery;2023 7th International Conference on Transportation Information and Safety (ICTIS);2023-08-04