{"title":"Active Reinforcement Learning for the Semantic Segmentation of Urban Images","authors":"Mahya Jodeiri Rad, Costas Armenakis","doi":"10.1080/07038992.2024.2374788","DOIUrl":null,"url":null,"abstract":"Image segmentation using supervised learning algorithms usually requires large amounts of annotated training data, while urban datasets frequently contain unbalanced classes leading to poor detecti...","PeriodicalId":48843,"journal":{"name":"Canadian Journal of Remote Sensing","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Canadian Journal of Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/07038992.2024.2374788","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0
Abstract
Image segmentation using supervised learning algorithms usually requires large amounts of annotated training data, while urban datasets frequently contain unbalanced classes leading to poor detecti...
期刊介绍：
Canadian Journal of Remote Sensing / Journal canadien de télédétection is a publication of the Canadian Aeronautics and Space Institute (CASI) and the official journal of the Canadian Remote Sensing Society (CRSS-SCT).
Canadian Journal of Remote Sensing provides a forum for the publication of scientific research and review articles. The journal publishes topics including sensor and algorithm development, image processing techniques and advances focused on a wide range of remote sensing applications including, but not restricted to; forestry and agriculture, ecology, hydrology and water resources, oceans and ice, geology, urban, atmosphere, and environmental science. Articles can cover local to global scales and can be directly relevant to the Canadian, or equally important, the international community. The international editorial board provides expertise in a wide range of remote sensing theory and applications.
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