{"title":"基于改进的更快R-CNN的目标高精度水平区域检测","authors":"Yu Liu, Dejun Li, Xiao Sun, Jian Chen, Zhaohong Xu","doi":"10.1117/12.2667441","DOIUrl":null,"url":null,"abstract":"Aiming at the multi-scale, multi-directional and deformation of targets in remote sensing images, a Fast R-CNN algorithm with deformable convolution is proposed in this paper, which can significantly improve the detection accuracy of ship targets and shorten the processing time.According to the characteristics of large aspect ratio of ships, the size and ratio of anchor frame are adjusted by the K-means clustering method , so that the improved algorithm is more suitable for detecting approximately vertical or horizontal objects, and can obtain high-precision horizontal region detection of ship targets.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Target high precision horizontal region detection based on improved faster R-CNN\",\"authors\":\"Yu Liu, Dejun Li, Xiao Sun, Jian Chen, Zhaohong Xu\",\"doi\":\"10.1117/12.2667441\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the multi-scale, multi-directional and deformation of targets in remote sensing images, a Fast R-CNN algorithm with deformable convolution is proposed in this paper, which can significantly improve the detection accuracy of ship targets and shorten the processing time.According to the characteristics of large aspect ratio of ships, the size and ratio of anchor frame are adjusted by the K-means clustering method , so that the improved algorithm is more suitable for detecting approximately vertical or horizontal objects, and can obtain high-precision horizontal region detection of ship targets.\",\"PeriodicalId\":128051,\"journal\":{\"name\":\"Third International Seminar on Artificial Intelligence, Networking, and Information Technology\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Third International Seminar on Artificial Intelligence, Networking, and Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2667441\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2667441","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Target high precision horizontal region detection based on improved faster R-CNN
Aiming at the multi-scale, multi-directional and deformation of targets in remote sensing images, a Fast R-CNN algorithm with deformable convolution is proposed in this paper, which can significantly improve the detection accuracy of ship targets and shorten the processing time.According to the characteristics of large aspect ratio of ships, the size and ratio of anchor frame are adjusted by the K-means clustering method , so that the improved algorithm is more suitable for detecting approximately vertical or horizontal objects, and can obtain high-precision horizontal region detection of ship targets.