现代电子技术2024，Vol.47Issue(17)：98-104,7.DOI:10.16652/j.issn.1004-373x.2024.17.016
海浪上下文信息补偿小目标检测算法
Wave context information compensation for small object detection algorithm
摘要
Abstract
In the images of maritime search and rescue,the area of the victims exposed on the water surface is not big enough and is susceptible to harsh environments such as reflections from waves and adverse weather conditions(rainy,foggy,etc.),which makes the image feature extraction difficult.In view of this,a scheme of wave context information compensation for small object detection algorithm is proposed.A sliding-window-based image preprocessing module is employed to crop the image so that the focus is concentrated on the object.The irrelevant area of the image is reduced,which lowers computational load and enhances the accuracy rate.A wave context module is proposed.It is for the first time by analyzing the motion direction and intensity of waves to extract the wave contextual information to assist in detecting small objects in maritime search and rescue scenarios and improving the detection accuracy.The experimental results on datasets SeaDronesSee v1 and SeaDronesSee v2 demonstrate that the proposed algorithm achieves an average precision of 73.29%and 87.81%,respectively.In comparison with the YOLOv7-tiny algorithm,the proposed method exhibits an average precision improvement of 21.84%and 6.5%on the two datasets.To sum up,the proposed algorithm significantly improves the detection accuracy of small objects in the scenarios of maritime search and rescue and raise the efficiency of maritime search and rescue.关键词
卷积神经网络/目标检测/无人机/海上搜救/上下文信息/YOLOv7-tinyKey words
convolutional neural network/object detection/unmanned aerial vehicle/maritime search and rescue/contextual information/YOLOv7-tiny分类
信息技术与安全科学引用本文复制引用
李世宝,李晨,李作志,王兆宇,贾泽昆..海浪上下文信息补偿小目标检测算法[J].现代电子技术,2024,47(17):98-104,7.基金项目
国家自然科学基金项目(61972417) （61972417）
山东省自然科学基金项目(ZR2020MF005,ZR2023LZH010) （ZR2020MF005,ZR2023LZH010）
