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Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
自动化研究所 [284]
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期刊论文 [761]
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A refined method for the simulation of catchment rainfall-runoff based on satellite-precipitation downscaling
期刊论文
OAI收割
JOURNAL OF HYDROLOGY, 2025, 卷号: 653, 页码: 15
作者:
Jian, Jihao
;
He, Siming
;
Liu, Wei
;
Liu, Shuang
;
Guo, Liping
  |  
收藏
  |  
浏览/下载:23/0
  |  
提交时间:2025/03/24
Deep Learning
Precipitation Downscaling Model
Rainfall-induced Runoff Simulation
Terrain-based Attention Mechanism
AIAM: Adaptive interactive attention model for solving p-Median problem via deep reinforcement learning
期刊论文
OAI收割
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2025, 卷号: 138, 页码: 104454
作者:
Liang, Haojian
;
Wang, Shaohua
;
Li, Huilai
;
Pan, Jie
;
Li, Xiao
  |  
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2025/04/21
PMP
Deep reinforcement learning
Adaptive Interactive Attention Model
Encoder-decoder
ACWCD: Utilizing Inherent Transformers Information and Prior Knowledge for Weakly Supervised Change Detection
期刊论文
OAI收割
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2025, 卷号: 63, 页码: 4402614
作者:
Liu, Wenhao
;
Yu, Zhuoyuan
;
Luo, Bin
  |  
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2025/03/18
Cams
Transformers
Feature extraction
Neural networks
Training
Data mining
Remote sensing
Refining
Deep learning
Decoding
Change detection (CD)
class activation maps (CAMs)
deep learning
high-resolution images
multihead self-attention (MHSA)
prior knowledge
transformers
weakly supervised learning
Quickly forecasting the future state of urban sensors by the missing-data-tolerant deep learning approach
期刊论文
OAI收割
SUSTAINABLE CITIES AND SOCIETY, 2025, 卷号: 118, 页码: 106044
作者:
Wang, Peixiao
;
Zhang, Hengcai
;
Cheng, Shifen
;
Zhang, Tong
;
Lu, Feng
  |  
收藏
  |  
浏览/下载:5/0
  |  
提交时间:2025/02/24
Spatiotemporal prediction
Spatiotemporal data missing
Causal dilatation convolution
Graph attention network
Predicting origin-destination flows by considering heterogeneous mobility patterns
期刊论文
OAI收割
SUSTAINABLE CITIES AND SOCIETY, 2025, 卷号: 118, 页码: 106015
作者:
Zhao, Yibo
;
Cheng, Shifen
;
Gao, Song
;
Wang, Peixiao
;
Lu, Feng
  |  
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2025/02/24
Origin-destination flow
Spatial interaction
Urban mobility
Spatial heterogeneity
Imbalanced data learning
Graph attention network
DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection
期刊论文
OAI收割
REMOTE SENSING, 2025, 卷号: 17, 期号: 2, 页码: 30
作者:
Lin, Shaofu
;
Yang, Yang
;
Liu, Xiliang
;
Tian, Li
  |  
收藏
  |  
浏览/下载:7/0
  |  
提交时间:2025/03/31
high-resolution images
photovoltaic
swin-transformer
dynamic spatial-frequency attention
Revealing the City Influence and Its Pattern Using Web Search Data: A New Perspective Through Attention Flow
期刊论文
OAI收割
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2025, 卷号: 14, 期号: 1, 页码: 22
作者:
Wang, Xiaoxiao
;
Zhang, Haiping
;
Li, Zitong
;
Yang, Xin
;
Qian, Ziyi
  |  
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2025/03/31
city influence
city association
spatial structure
social sensing
attention flow
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:64/0
  |  
提交时间:2024/02/19
Residual network
graph attention network
super-pixel segmentation
habitat quality
driving force analysis
Attention Swin Transformer UNet for Landslide Segmentation in Remotely Sensed Images
期刊论文
OAI收割
REMOTE SENSING, 2024, 卷号: 16, 期号: 23, 页码: 4464
作者:
Liu, Bingxue
;
Wang, Wei
;
Wu, Yuming
;
Gao, Xing
  |  
收藏
  |  
浏览/下载:9/0
  |  
提交时间:2025/01/17
remote sensing (RS)
landslide segmentation
attention mechanism
spatial detailed information
Local context attention learning for fine-grained scene graph generation
期刊论文
OAI收割
PATTERN RECOGNITION, 2024, 卷号: 156, 页码: 13
作者:
Zhu, Xuhan
;
Wang, Ruiping
;
Lan, Xiangyuan
;
Wang, Yaowei
  |  
收藏
  |  
浏览/下载:1/0
  |  
提交时间:2024/12/06
Fine-grained scene graph generation
Local context
Location attention network
Local context-consistent label transfer