数字海洋与水下攻防2024，Vol.7Issue(3)：334-341,8.DOI:10.19838/j.issn.2096-5753.2024.03.012
基于多模态感知的水下目标检测应用构想
Research on Application of Underwater Object Detection Based on Multimodal Perception
陈悦 1罗逸豪 1李锦2
作者信息
- 1. 清江创新中心,湖北 武汉 430200||中国船舶集团有限公司第七一〇研究所,湖北 宜昌 443003
- 2. 海军工程大学 基础部,湖北 武汉 430033
- 折叠
摘要
Abstract
Underwater object detection has been widely applied in various fields,such as marine biology research,archaeological exploration,and military defense.With the rapid development of artificial intelligence,underwater object detection has also become unmanned and intelligent.Deep learning uses neural networks to mine information features,demonstrating excellent performance in both speed and accuracy,and has become the mainstream algorithm in computer vision technology.However,in complex underwater environments,there are still significant challenges in applying it to underwater image object detection.The complementary information and rich features of various modalities of underwater targets are beneficial for target detection and recognition.Therefore,this article combines application scenarios to investigate existing technologies,and then designs a multimodal underwater target detection system based on deep learning.At the same time,the advantages and disadvantages of existing core technologies are compared and analyzed.Finally,a summary and outlook on the future development of multimodal object detection systems are carried out,which is of great significance.关键词
水下目标检测/深度学习/多模态Key words
underwater object detection/deep learning/multimodal分类
信息技术与安全科学引用本文复制引用
陈悦,罗逸豪,李锦..基于多模态感知的水下目标检测应用构想[J].数字海洋与水下攻防,2024,7(3):334-341,8.
