{"title":"星火挑战:空间目标识别的多模态分类器","authors":"I. Lahouli, M. Jarraya, G. Aversano","doi":"10.1109/ICIPC53495.2021.9620183","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a multi-modal framework to tackle the SPARK Challenge by classifying satellites using RGB and depth images. Our framework is mainly based on Auto-Encoders (AE)s to embed the two modalities in a common latent space in order to exploit redundant and complementary information between the two types of data.","PeriodicalId":246438,"journal":{"name":"2021 IEEE International Conference on Image Processing Challenges (ICIPC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Spark Challenge: Multimodal Classifier for Space Target Recognition\",\"authors\":\"I. Lahouli, M. Jarraya, G. Aversano\",\"doi\":\"10.1109/ICIPC53495.2021.9620183\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a multi-modal framework to tackle the SPARK Challenge by classifying satellites using RGB and depth images. Our framework is mainly based on Auto-Encoders (AE)s to embed the two modalities in a common latent space in order to exploit redundant and complementary information between the two types of data.\",\"PeriodicalId\":246438,\"journal\":{\"name\":\"2021 IEEE International Conference on Image Processing Challenges (ICIPC)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Image Processing Challenges (ICIPC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIPC53495.2021.9620183\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Image Processing Challenges (ICIPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIPC53495.2021.9620183","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spark Challenge: Multimodal Classifier for Space Target Recognition
In this paper, we propose a multi-modal framework to tackle the SPARK Challenge by classifying satellites using RGB and depth images. Our framework is mainly based on Auto-Encoders (AE)s to embed the two modalities in a common latent space in order to exploit redundant and complementary information between the two types of data.
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