伪装
人工智能
目标检测
计算机科学
深度学习
对象(语法)
计算机视觉
模式识别(心理学)
作者
Yong Wang,Ling Li,Xin Yang,Xinxin Wang,Hui Liu
标识
DOI:10.1109/icaiis49377.2020.9194881
摘要
Camouflaged object detection is a hard assignment due to their textures are similar to the background. The main intention of this paper is probe into a problem about the camouflaged object detection, that is, detecting its camouflaged object for a given image. This problem has not been well studied in spite of a large area of potential applications such as camouflage military targets detection and wildlife protection. To address this problem, a camouflage object detection method based on deep learning is proposed. The suggested method can detect camouflaged object which can extract deep features automatically. It can also provide detection probability which reflect camouflage efficiency. Experimental results show that the deep learning measure can effectively detect different scene, representing the camouflage level of low, medium and high respectively.
科研通智能强力驱动
Strongly Powered by AbleSci AI