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In this paper, we present the supervised multi-view canonical correlation analysis ensemble (SMVCCAE) and its semi-supervised version (SSMVCCAE), which are novel techniques designed to address heterogeneous domain adaptation problems, i.e., situations in which the data to be processed and recognized are collected from different heterogeneous domains.(More)
Alim Samat 1,2,*, Paolo Gamba 3, Jilili Abuduwaili 1,2, Sicong Liu 4 and Zelang Miao 5 1 State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; jilil@ms.xjb.ac.cn 2 Chinese Academy of Sciences Research Center for Ecology and Environment of Central Asia, Urumqi 830011,(More)
Oil spill monitoring in optical remote sensing (RS) images is a challenging task due to the complexity of target discrimination in an oil spill scenario. Differently from traditional oil spill detection methods that are mainly carried out in a monotemporal image, in this letter, a novel solution is given in a multitemporal domain by investigating potential(More)
Scene classification from remote sensing images provides new possibilities for potential application of high spatial resolution imagery. How to efficiently implement scene recognition from high spatial resolution imagery remains a significant challenge in the remote sensing domain. Recently, convolutional neural networks (CNN) have attracted tremendous(More)
Considering the important roles of carbonate rock fraction in karst rocky desertification areas and their potential for indicating damage to vegetation, improved knowledge is desired to assess the application of spectroscopy and remote sensing to characterizing and quantifying the biophysical constituents of karst landscapes. In this study, we examined the(More)
Based on annual average PM2.5 gridded dataset, this study first analyzed the spatiotemporal pattern of PM2.5 across Mainland China during 1998-2012. Then facilitated with meteorological site data, land cover data, population and Gross Domestic Product (GDP) data, etc., the contributions of latent geographic factors, including socioeconomic factors (e.g.,(More)
This paper proposes to use band selection-based dimensionality reduction (BS-DR) technique in addressing a challenging multi-temporal hyperspectral images change detection (HSI-CD) problem. The aim of this work is to analyze and evaluate in detail the CD performance by selecting the most informative band subset from the original high-dimensional data space.(More)