JOURNAL ARTICLE

Ship Detection from Optical Satellite Images with Deep Learning

Abstract

The effective use and control of maritime routes in the commercial/military area is an increasing and important need for states. There are some motivations for this purpose: Safe traffic of the ships in narrow canals, avoiding illegal usage of anchoring areas of ships, monitoring fishing activities to avoid illegal fishing or protect fish population, detection of lost ships, boats or debris in the ocean, detection and identification of warships (intelligence, defense, offensive, etc.). This paper proposed an open source, fast running ship detection system from optical satellite images with the deep learning algorithm. The system does not need any comprehensive hardware, even can work on an average laptop. Tensorflow Object Detection Application Programming Interface (API)is trained by optical satellite images with ships and used as object detection API.

Keywords:
Laptop Computer science Object detection Satellite Population Remote sensing Interface (matter) Artificial intelligence Deep learning Computer security Computer vision Engineering Geography Pattern recognition (psychology)

Metrics

20
Cited By
1.52
FWCI (Field Weighted Citation Impact)
14
Refs
0.84
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Remote-Sensing Image Classification
Physical Sciences →  Engineering →  Media Technology
Infrared Target Detection Methodologies
Physical Sciences →  Engineering →  Aerospace Engineering
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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