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
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遥感与数字地球研... [329]
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Assessment of the urban habitat quality service functions and their drivers based on the fusion module of graph attention network and residual network
期刊论文
OAI收割
INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2024, 卷号: 17, 期号: 1, 页码: 29
作者:
Wang, Chunyang
;
Yang, Kui
;
Yang, Wei
;
Li, Runkui
;
Qiang, Haiyang
  |  
收藏
  |  
浏览/下载:13/0
  |  
提交时间:2024/02/19
Residual network
graph attention network
super-pixel segmentation
habitat quality
driving force analysis
Unleashing the full potential of hyperspectral imaging: Decoupled image and frequency-domain spatial-spectral framework
期刊论文
OAI收割
EXPERT SYSTEMS WITH APPLICATIONS, 2024, 卷号: 243, 页码: 20
作者:
He, Shuang
;
Tian, Jia
;
Hao, Lina
;
Zhang, Sen
;
Tian, Qingjiu
  |  
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2024/02/18
Frequency domain
Feature extraction
Cross-domain fusion
Hyperspectral image classification
A reversible data hiding method based on bitmap prediction for AMBTC compressed hyperspectral images
期刊论文
OAI收割
JOURNAL OF INFORMATION SECURITY AND APPLICATIONS, 2024, 卷号: 81, 页码: 15
作者:
Zhang, Xiaoran
;
Pan, Zhibin
;
Zhou, Quan
;
Fan, Guojun
;
Dong, Jing
  |  
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2024/03/27
Absolute moment block truncation coding
(AMBTC)
Hyperspectral images
Reversible data hiding (RDH)
Prediction of bitmap
Adaptive embedding order
Dynamical embedding scheme
A reversible data hiding method based on bitmap prediction for AMBTC compressed hyperspectral images
期刊论文
OAI收割
JOURNAL OF INFORMATION SECURITY AND APPLICATIONS, 2024, 卷号: 81
作者:
Zhang, Xiaoran
;
Pan, Zhibin
;
Zhou, Quan
;
Fan, Guojun
;
Dong, Jing
  |  
收藏
  |  
浏览/下载:14/0
  |  
提交时间:2024/03/26
Absolute moment block truncation coding
(AMBTC)
Hyperspectral images
Reversible data hiding (RDH)
Prediction of bitmap
Adaptive embedding order
Dynamical embedding scheme
Learning transferable cross-modality representations for few-shot hyperspectral and LiDAR collaborative classification
期刊论文
OAI收割
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2024, 卷号: 126, 页码: 11
作者:
Dai, Mofan
;
Xing, Shuai
;
Xu, Qing
;
Wang, Hanyun
;
Li, Pengcheng
  |  
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2024/02/26
Multimodal remote sensing data
Meta-learning
Few-shot learning
Cross-modality feature learning
Methodology and Modeling of UAV Push-Broom Hyperspectral BRDF Observation Considering Illumination Correction
期刊论文
OAI收割
REMOTE SENSING, 2024, 卷号: 16, 期号: 3
作者:
Wang, Zhuo
;
Li, Haiwei
;
Wang, Shuang
;
Song, Liyao
;
Chen, Junyu
  |  
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2024/03/15
UAV
push-broom hyperspectral
BRDF model improvement
data coupling
illumination correction factor
Discrimination of the degree of heavy metal pollution in corn leaves in mining areas based on semi-supervised learning
期刊论文
OAI收割
REMOTE SENSING LETTERS, 2024, 卷号: 15, 期号: 1, 页码: 10-23
作者:
He, Jiale
;
Yang, Keming
;
Yang, Fei
;
Li, Yanru
;
Wu, Bing
  |  
收藏
  |  
浏览/下载:7/0
  |  
提交时间:2024/01/22
Corn leaves
heavy metal pollution
hyperspectral
semi-supervised learning
discriminant model
Multilevel-based algorithm for hyperspectral image interpretation
期刊论文
OAI收割
COMPUTERS & ELECTRICAL ENGINEERING, 2024, 卷号: 113, 页码: 109033
作者:
Qiu, Shi
;
Ye, Huping
;
Liao, Xiaohan
;
Zhang, Benyue
;
Zhang, Miao
  |  
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2024/01/04
Hyperspectrum
Interpretation
Attention
Feature association
Semantic
Multilevel-based algorithm for hyperspectral image interpretation
期刊论文
OAI收割
Computers and Electrical Engineering, 2024, 卷号: 113
作者:
Qiu, Shi
;
Ye, Huping
;
Liao, Xiaohan
;
Zhang, Benyue
;
Zhang, Miao
  |  
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2024/01/03
Hyperspectrum
Interpretation
Attention
Feature association
Semantic
Rapid Determination of Positive-Negative Bacterial Infection Based on Micro-Hyperspectral Technology
期刊论文
OAI收割
SENSORS, 2024, 卷号: 24, 期号: 2
作者:
Du, Jian
;
Tao, Chenglong
;
Qi, Meijie
;
Hu, Bingliang
;
Zhang, Zhoufeng
  |  
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2024/03/04
micro-hyperspectral technology
bacterial infection
positive-negative determination
spectral feature
directly smeared urine sample
deep learning