火力与指挥控制2025，Vol.50Issue(2)：1-12,20,13.DOI:10.3969/j.issn.1002-0640.2025.02.001
基于深度学习的伪装目标检测研究进展
Research Progress on Camouflaged Object Detection Based on Deep Learning
张冬冬 1王春平 1付强 1王慧赢1
作者信息
- 1. 陆军工程大学石家庄校区,石家庄 050003
- 折叠
摘要
Abstract
Camouflaged object detection is an emerging research direction that has attracted wide attention in the field of computer vision.However,most existing works focus on building efficient detection models,lacking in-depth analysis and summarization of the existing models.Therefore,the existing deep learning-based camouflaged object detection models are comprehensively analyzed and summarized.And the potential research directions of camouflaged object detection are explored.Firstly,a comprehensive review of existing deep learning-based models is conducted,the principles and advantages/disadvantages of the related models are expounded in detail.Secondly,the commonly used datasets and evaluation metrics in the camouflaged object detection field are introduced.Next,the existing deep learning-based camouflaged object detection models are reproduced,and qualitative and quantitative comparisons of different types of models are performed on public datasets.Finally,the it is summarized and the future research directions in the field of camouflaged object detection are prospected.关键词
伪装目标检测/深度学习/数据集/评价指标Key words
camouflaged object/deep learning/dataset/evaluation metrics分类
计算机与自动化引用本文复制引用
张冬冬,王春平,付强,王慧赢..基于深度学习的伪装目标检测研究进展[J].火力与指挥控制,2025,50(2):1-12,20,13.
