Ship detection in optical sensing images based on YOLOv5
Yu‐Wen Chen, Chao Zhang, Tengfei Qiao, Jian-Lin Xiong, Bin Liu
Abstract
Ship detection technology is an important development direction in the field of optical remote sensing image processing. In recent years, convolutional neural networks have achieved good results in ship target detection and recognition. We train the latest model YOLOv5 on our dataset in this paper. The results show that YOLOv5 can be well applied in the field of ship detection.
Topics & Concepts
Computer scienceComputer visionArtificial intelligenceRemote sensingGeologyAdvanced Neural Network Applications