4 Papers
Jiaming Liu is an academic researcher from University of Electronic Science and Technology of China. The author has contributed to research in topics: Concept drift & Data stream mining. The author has an hindex of 3, co-authored 4 publications.
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Papers
A spatiotemporal deep fusion model for merging satellite and gauge precipitation in China
TL;DR: In this article, a deep fusion model is proposed to merge the TRMM 3B42 V7 satellite data, rain gauge data and thermal infrared images by exploiting their spatial and temporal correlations simultaneously.
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Online reliable semi-supervised learning on evolving data streams
TL;DR: A new online semi-supervised learning algorithm is proposed by modeling concept drifts with a set of micro-clusters that are dynamically maintained to capture the evolving concepts with error-based representative learning and yield high classification performance compared to many state-of-the-art algorithms.
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Selective prototype-based learning on concept-drifting data streams
TL;DR: Experimental results show that the SPL has better classification performance than many other state-of-the-art algorithms, and has great capabilities to distinguish noise/outliers from drifting instances.
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Dynamic Attribution Analysis for Runoff Change Integrating Landsat-Derived Land Use Dynamics with Swat Model
Shasha Luo,Qinli Yang,Hongcai Wu,Jiaming Liu,Guoqing Wang,Yong Wang,Yuanyuan Yang +6 more
- 01 Jul 2019
TL;DR: In this article, the authors quantified the inter-annual attribution of runoff change in the Qingliu River, China and found that runoff increased insignificantly during 1960-2012 and changed abruptly in 1984.
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