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Key-Part Attention Retrieval for Robotic Object Recognition
期刊论文
TSINGHUA SCIENCE AND TECHNOLOGY, 2024, 卷号: 29, 期号: 3, 页码: 644-655
作者:
Liu, Jierui
;
Cao, Zhiqiang
;
Tang, Yingbo
收藏
  |  
浏览/下载:11/0
  |  
提交时间:2024/02/22
Training
Visualization
Image recognition
Cameras
Object recognition
Convolutional neural networks
Data mining
key-part attention
retrieval
robotic object recognition
Super Resolution Graph With Conditional Normalizing Flows for Temporal Link Prediction
期刊论文
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2024, 卷号: 36, 期号: 3, 页码: 1311-1327
作者:
Yin, Yanting
;
Wu, Yajing
;
Yang, Xuebing
;
Zhang, Wensheng
;
Yuan, Xiaojie
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2024/05/30
Noise measurement
Feature extraction
Task analysis
Superresolution
Data mining
Predictive models
Information processing
Temporal link prediction
dynamic graphs
super-resolution
conditional normalizing flow
SpatioTemporal Inference Network for Precipitation Nowcasting With Multimodal Fusion
期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2024, 卷号: 17, 页码: 1299-1314
作者:
Jin, Qizhao
;
Zhang, Xinbang
;
Xiao, Xinyu
;
Wang, Ying
;
Meng, Gaofeng
收藏
  |  
浏览/下载:13/0
  |  
提交时间:2024/02/21
Data mining
multimodal knowledge discovery
precipitation nowcasting
Preformer: Simple and Efficient Design for Precipitation Nowcasting With Transformers
期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2024, 卷号: 21, 页码: 5
作者:
Jin, Qizhao
;
Zhang, Xinbang
;
Xiao, Xinyu
;
Wang, Ying
;
Xiang, Shiming
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  |  
浏览/下载:5/0
  |  
提交时间:2024/03/26
Data mining
Precipitation nowcastin
Transformer
A lightweight convolutional neural network with end-to-end learning for three-dimensional mineral prospectivity modeling: A case study of the Sanhetun Area, Heilongjiang Province, Northeastern China
期刊论文
ORE GEOLOGY REVIEWS, 2023, 卷号: 163, 页码: 20
作者:
Zhang, Baoyi
;
Xu, Kun
;
Khan, Umair
;
Li, Xuefeng
;
Du, Linze
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  |  
浏览/下载:6/0
  |  
提交时间:2024/01/22
3D geological models
Convolutional neural networks
Deconvolution
Weight of evidence
3D mineral prospectivity modeling
Application of Social Sensors in Natural Disasters Emergency Management: A Review
期刊论文
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2023, 卷号: 10, 期号: 6, 页码: 3143-3158
作者:
Shi, Kaize
;
Peng, Xueping
;
Lu, Hao
;
Zhu, Yifan
;
Niu, Zhendong
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  |  
浏览/下载:1/0
  |  
提交时间:2024/07/03
Sensors
Emergency services
Sentiment analysis
Social networking (online)
Sensor phenomena and characterization
Intelligent sensors
Earthquakes
Decision support system
emergency management
parallel system
social network analysis
social sensor
sudden natural disaster
Consistent Matrix: A Feature Selection Framework for Large-Scale Datasets
期刊论文
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2023, 卷号: 31, 期号: 11, 页码: 4024-4038
作者:
Yang, Tian
;
Li, Yuan-Jiang
;
Qian, Yuhua
;
Wang, Fei-Yue
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  |  
浏览/下载:4/0
  |  
提交时间:2024/02/22
Consistent matrix
feature selection
fuzzy arithmetic covering
fuzzy rough sets
granular computing
Applications of remote sensing and near-surface geophysical methods for the investigations of a morainic ridge susceptible to landslide. A case study from the high lands of the Himalayas, Pakistan
期刊论文
JOURNAL OF APPLIED GEOPHYSICS, 2023, 卷号: 217, 页码: 15
作者:
Ullah, Faheem
;
Su, Lijun
;
Alam, Mehtab
;
Cheng, Li
;
Kazantseva, Elena S.
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2024/02/27
ERT
MASW
GPR
Remote sensing
Landslide
CRule: Category-Aware Symbolic Multihop Reasoning on Knowledge Graphs
期刊论文
IEEE INTELLIGENT SYSTEMS, 2023, 卷号: 38, 期号: 5, 页码: 56-64
作者:
Wang, Zikang
;
Li, Linjing
;
Li, Jinlin
;
Zhao, Pengfei
;
Zeng, Daniel
收藏
  |  
浏览/下载:5/0
  |  
提交时间:2023/11/15
Cognition
Intelligent systems
Spread spectrum communication
Data mining
Computational modeling
Complexity theory
Knowledge graphs
Latent Structure Mining With Contrastive Modality Fusion for Multimedia Recommendation
期刊论文
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2023, 卷号: 35, 期号: 9, 页码: 9154-9167
作者:
Zhang, Jinghao
;
Zhu, Yanqiao
;
Liu, Qiang
;
Zhang, Mengqi
;
Wu, Shu
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2023/11/17
Multimedia recommendation
graph structure learning
contrastive learning
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