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科研机构
湖南大学 [17]
内容类型
期刊论文 [17]
发表日期
2018 [17]
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共17条,第1-10条
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发表日期:2018
内容类型:期刊论文
专题:湖南大学
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Deformable Convolutional Neural Networks for Hyperspectral Image Classification
期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2018, 卷号: Vol.15 No.8, 页码: 1254-1258
作者:
Zhu, Jian
;
Fang, Leyuan
;
Ghamisi, Pedram
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2019/12/26
Convolutional neural networks (CNNs)
deformable convolution
hyperspectral image (HSI) classification
spatial-spectral feature extraction
Remote Sensing Scene Classification Using Multilayer Stacked Covariance Pooling
期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2018, 卷号: Vol.56 No.12, 页码: 6899-6910
作者:
He, NJ
;
Fang, LY
;
Li, ST
;
Plaza, A
;
Plaza, J
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2019/12/26
Feature fusion
multilayer feature maps
pre-trained convolutional neural networks (CNN)
remote sensing scene classification
Remote Sensing Scene Classification Using Multilayer Stacked Covariance Pooling
期刊论文
IEEE Transactions on Geoscience and Remote Sensing, 2018, 卷号: Vol.56 No.12, 页码: 6899-6910
作者:
Nanjun He
;
Leyuan Fang
;
Shutao Li
;
Antonio Plaza
;
Javier Plaza
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2019/12/26
Feature extraction
Remote sensing
Nonhomogeneous media
Support vector machines
Covariance matrices
Computational modeling
Semantics
Feature fusion
multilayer feature maps
pretrained convolutional neural networks (CNN)
remote sensing scene classification
Hyperspectral Image Classification with Deep Feature Fusion Network
期刊论文
IEEE Transactions on Geoscience and Remote Sensing, 2018, 卷号: Vol.56 No.6, 页码: 3173-3184
作者:
Song, W.
;
Li, S.
;
Fang, L.
;
Lu, T.
收藏
  |  
浏览/下载:1/0
  |  
提交时间:2019/12/26
Convolutional neural networks (CNNs)
feature fusion
hyperspectal image classification
residual learning
Deep Learning in Medical Image Analysis and Its Challenges
期刊论文
Zidonghua Xuebao/Acta Automatica Sinica, 2018, 卷号: Vol.44 No.3, 页码: 401-424
作者:
Tian, J.-X.
;
Liu, G.-C.
;
Gu, S.-S.
;
Ju, Z.-J.
;
Liu, J.-G.
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2019/12/26
Convolutional neural networks (CNNs)
Deep learning (DL)
Image classification
Image segmentation
Medical image analysis
Remote sensing scene classification using multilayer stacked covariance pooling
期刊论文
IEEE Transactions on Geoscience and Remote Sensing, 2018, 卷号: Vol.56 No.12, 页码: 6899-6910
作者:
He, N.
;
Fang, L.
;
Li, S.
;
Plaza, A.
;
Plaza, J.
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2019/12/26
Feature fusion
multilayer feature maps
pretrained convolutional neural networks (CNN)
remote sensing scene classification
Remote Sensing Scene Classification Using Multilayer Stacked Covariance Pooling.
期刊论文
IEEE Transactions on Geoscience & Remote Sensing, 2018, 卷号: Vol.56 No.12, 页码: 6899-6910
作者:
He, Nanjun
;
Fang, Leyuan
;
Li, Shutao
;
Plaza, Antonio
;
Plaza, Javier
收藏
  |  
浏览/下载:7/0
  |  
提交时间:2019/12/26
Computational modeling
Covariance matrices
Feature extraction
Feature fusion
multilayer feature maps
Nonhomogeneous media
pretrained convolutional neural networks (CNN)
Remote sensing
remote sensing scene classification
Semantics
Support vector machines
Hyperspectral Image Classification With Deep Feature Fusion Network.
期刊论文
IEEE Transactions on Geoscience & Remote Sensing, 2018, 卷号: Vol.56 No.6, 页码: 3173-3184
作者:
Song, Weiwei
;
Li, Shutao
;
Fang, Leyuan
;
Lu, Ting
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2019/12/26
Convolutional neural networks
Convolutional neural networks (CNNs)
Feature extraction
feature fusion
hyperspectal image classification
Hyperspectral imaging
Logistics
residual learning
Support vector machines
Training
Ensemble feature learning for material recognition with convolutional neural networks
期刊论文
EURASIP Journal on Image and Video Processing, 2018, 卷号: Vol.2018 No.1, 页码: 64
作者:
Peng Bian
;
Wanwan Li
;
Yi Jin
;
Ruicong Zhi
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2019/12/26
Deep Hyperspectral Image Sharpening
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: Vol.29 No.11, 页码: 5345-5355
作者:
Dian, Renwei
;
Li, Shutao
;
Guo, Anjing
;
Fang, Leyuan
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2019/12/26
Deep convolutional neural network (CNN) fusion
hyperspectral imaging
residual learning
super-resolution
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