Ship Detection in Optical Sensing Images Based on Yolov5

被引：35

作者：

Chen, Yuwen ^{[1
]}

Zhang, Chao ^{[1
]}

Qiao, Tengfei ^{[1
]}

Xiong, Jianlin ^{[1
]}

Liu, Bin ^{[1
]}

机构：

[1] Beijing Res Inst Telemetry, Beijing 100094, Peoples R China

来源：

TWELFTH INTERNATIONAL CONFERENCE ON GRAPHICS AND IMAGE PROCESSING (ICGIP 2020) | 2021年 / 11720卷

关键词：

Ship detection; optical remote sensing image processing; YOLOv5;

D O I：

10.1117/12.2589395

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

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.

引用

页数：5

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