{"title":"无人机运动趋势增强二维检测研究","authors":"Hao Wu","doi":"10.1109/CCAI57533.2023.10201284","DOIUrl":null,"url":null,"abstract":"Inspired by the human visual system, we proposed a motion information-based enhancement mechanism for drone detection, named Collaborative Filtering Mechanism (CFM). CFM enhances small object features through GAN-based image translation which is based on a Cycle Generative Adversarial Network (CycleGAN), and filters out unrelated features during the feature extraction cascade of YOLO-V5s, thus improving the performance of object detection. In the experiments, we verified the performance improvement brought by the proposed CFM module on the VisDrone dataset.","PeriodicalId":285760,"journal":{"name":"2023 IEEE 3rd International Conference on Computer Communication and Artificial Intelligence (CCAI)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Motion Trend Enhanced 2D Detection on Drones\",\"authors\":\"Hao Wu\",\"doi\":\"10.1109/CCAI57533.2023.10201284\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Inspired by the human visual system, we proposed a motion information-based enhancement mechanism for drone detection, named Collaborative Filtering Mechanism (CFM). CFM enhances small object features through GAN-based image translation which is based on a Cycle Generative Adversarial Network (CycleGAN), and filters out unrelated features during the feature extraction cascade of YOLO-V5s, thus improving the performance of object detection. In the experiments, we verified the performance improvement brought by the proposed CFM module on the VisDrone dataset.\",\"PeriodicalId\":285760,\"journal\":{\"name\":\"2023 IEEE 3rd International Conference on Computer Communication and Artificial Intelligence (CCAI)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE 3rd International Conference on Computer Communication and Artificial Intelligence (CCAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCAI57533.2023.10201284\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 3rd International Conference on Computer Communication and Artificial Intelligence (CCAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCAI57533.2023.10201284","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Motion Trend Enhanced 2D Detection on Drones
Inspired by the human visual system, we proposed a motion information-based enhancement mechanism for drone detection, named Collaborative Filtering Mechanism (CFM). CFM enhances small object features through GAN-based image translation which is based on a Cycle Generative Adversarial Network (CycleGAN), and filters out unrelated features during the feature extraction cascade of YOLO-V5s, thus improving the performance of object detection. In the experiments, we verified the performance improvement brought by the proposed CFM module on the VisDrone dataset.