城市图像语义分割的主动强化学习
IF 2
4区 地球科学
Q3 REMOTE SENSING
引用次数: 0
摘要
使用监督学习算法进行图像分割通常需要大量注释训练数据，而城市数据集经常包含不平衡的类别，导致检测效果不佳。本文章由计算机程序翻译，如有差异，请以英文原文为准。
Active Reinforcement Learning for the Semantic Segmentation of Urban Images
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...
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来源期刊
Canadian Journal of Remote Sensing
REMOTE SENSING-
自引率
3.80%
发文量
40
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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