中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
地理科学与资源研究所 [2]
长春光学精密机械与物... [1]
自动化研究所 [1]
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OAI收割 [4]
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Decision-Level and Feature-Level Integration of Remote Sensing and Geospatial Big Data for Urban Land Use Mapping
期刊论文
OAI收割
REMOTE SENSING, 2021, 卷号: 13, 期号: 8, 页码: 17
作者:
Yin, Jiadi
;
Fu, Ping
;
Hamm, Nicholas A. S.
;
Li, Zhichao
;
You, Nanshan
  |  
收藏
  |  
浏览/下载:46/0
  |  
提交时间:2021/06/10
urban land use
remote sensing
geospatial big data
decision-level integration
feature-level integration
Hangzhou
Decision-Level and Feature-Level Integration of Remote Sensing and Geospatial Big Data for Urban Land Use Mapping
期刊论文
OAI收割
REMOTE SENSING, 2021, 卷号: 13, 期号: 8, 页码: 17
作者:
Yin, Jiadi
;
Fu, Ping
;
Hamm, Nicholas A. S.
;
Li, Zhichao
;
You, Nanshan
  |  
收藏
  |  
浏览/下载:38/0
  |  
提交时间:2021/06/10
urban land use
remote sensing
geospatial big data
decision-level integration
feature-level integration
Hangzhou
Chinese Short Text Classification with Mutual-Attention Convolutional Neural Networks
期刊论文
OAI收割
ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING, 2020, 卷号: 19, 期号: 5, 页码: 13
作者:
Hao, Ming
;
Xu, Bo
;
Liang, Jing-Yi
;
Zhang, Bo-Wen
;
Yin, Xu-Cheng
  |  
收藏
  |  
浏览/下载:29/0
  |  
提交时间:2021/03/01
Short text classification
word-level and character-level
feature integration
mutual-attention
convolutional neural networks
Multiwavelet based multispectral image fusion for corona detection (EI CONFERENCE)
会议论文
OAI收割
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
作者:
Wang X.
;
Yang H.-J.
;
Sui Y.-X.
;
Yan F.
;
Yan F.
收藏
  |  
浏览/下载:31/0
  |  
提交时间:2013/03/25
Image fusion refers to the integration of complementary information provided by various sensors such that the new images are more useful for human or machine perception. Multiwavelet transform has simultaneous orthogonality
symmetry
compact support
and vanishing moment
which are not possible with scalar wavelet transform. Multiwavelet analysis can offer more precise image analysis than wavelet multiresolution analysis. In this paper
a new image fusion algorithm based on discrete multiwavelet transform (DMWT) to fuse the dual-spectral images generated from the corona detection system is presented. The dual-spectrum detection system is used to detect the corona and indicate its exact location. The system combines a solar-blind UV ICCD with a visible camera
where the UV image is useful for detecting UV emission from corona and the visible image shows the position of the corona. The developed fusion algorithm is proposed considering the feature of the UV and visible images adequately. The source images are performed at the pixel level. First
a decomposition step is taken with the DMWT. After the decomposition step
a pyramid for each source image in each level can be obtained. Then
an optimized coefficient fusion rule consisting of activity level measurement
coefficient combining and consistency verification is used to acquire the fused coefficients. This process reduces the impulse noise of UV image. Finally
a new fused image is obtained by reconstructing the fused coefficients using inverse DMWT. This image fusion algorithm has been applied to process the multispectral UV/visible images. Experimental results show that the proposed method outperforms the discrete wavelet transform based approach.