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资助机构:National Natural Science Foundation of China
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Combination of time domain-system matrix and x-space methods to reconstruct magnetic particle images with isotropic resolution
期刊论文
PHYSICS IN MEDICINE AND BIOLOGY, 2024, 卷号: 69, 期号: 3, 页码: 13
作者:
Shan, Shihao
;
Zhang, Chenglong
;
Yin, Lin
;
Yang, Xiaoli
;
Yu, Dexin
;
Qi, Yafei
;
Li, Min
;
Wildgruber, Moritz
;
Du, Yang
;
Tian, Jie
;
Ma, Xiaopeng
收藏
  |  
浏览/下载:93/0
  |  
提交时间:2024/02/20
magnetic particle imaging
x-space
isotropic resolution
time domain system matrix
medical image reconstruction
Seismic Random Noise Suppression Model Based on Downsampling and Superresolution
期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 卷号: 61, 页码: 14
作者:
Fang, Ziyi
;
Lin, Hongbo
;
Sun, Fuyao
;
Song, Xue
;
Zhang, Chao
;
Wang, Bo
收藏
  |  
浏览/下载:28/0
  |  
提交时间:2023/11/17
Noise reduction
Superresolution
Image restoration
Generators
Data models
Complexity theory
Signal resolution
Seismic exploration
seismic random noise
seismic signal denoising
superresolution (SR)
SSAU-Net: A Spectral-Spatial Attention-Based U-Net for Hyperspectral Image Fusion
期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 卷号: 60, 页码: 16
作者:
Liu, Shuaiqi
;
Liu, Siyuan
;
Zhang, Shichong
;
Li, Bing
;
Hu, Weiming
;
Zhang, Yu-Dong
收藏
  |  
浏览/下载:248/0
  |  
提交时间:2023/03/20
Feature extraction
Matrix decomposition
Image fusion
Hyperspectral imaging
Spatial resolution
Tensors
Image reconstruction
Deep learning
hyperspectral image (HSI)
image fusion
multispectral image (MSI)
spectral-spatial attention
PSGAN plus plus : Robust Detail-Preserving Makeup Transfer and Removal
期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2022, 卷号: 44, 期号: 11, 页码: 8538-8551
作者:
Liu, Si
;
Jiang, Wentao
;
Gao, Chen
;
He, Ran
;
Feng, Jiashi
;
Li, Bo
;
Yan, Shuicheng
收藏
  |  
浏览/下载:250/0
  |  
提交时间:2022/11/14
Faces
Generative adversarial networks
Task analysis
Visualization
Nose
Image resolution
Skin
Makeup transfer
makeup removal
generative adversarial networks
An Efficient Multiresolution Network for Vehicle Reidentification
期刊论文
IEEE INTERNET OF THINGS JOURNAL, 2022, 卷号: 9, 期号: 11, 页码: 9049-9059
作者:
Shen, Fei
;
Zhu, Jianqing
;
Zhu, Xiaobin
;
Huang, Jingchang
;
Zeng, Huanqiang
;
Lei, Zhen
;
Cai, Canhui
收藏
  |  
浏览/下载:268/0
  |  
提交时间:2022/07/25
Image resolution
Training
Feature extraction
Spatial resolution
Proposals
Internet of Things
Deep learning
Deep learning
image representation
multiresolution
vehicle reidentification
Theme-Aware Aesthetic Distribution Prediction With Full-Resolution Photographs
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 15
作者:
Jia, Gengyun
;
Li, Peipei
;
He, Ran
Adobe PDF(10845Kb)
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  |  
浏览/下载:279/41
  |  
提交时间:2022/06/06
Aesthetic quality assessment (AQA)
full resolution
region of image (RoM) pooling
theme
Super-resolution semantic segmentation with relation calibrating network
期刊论文
PATTERN RECOGNITION, 2022, 卷号: 124, 页码: 10
作者:
Jiang, Jie
;
Liu, Jing
;
Fu, Jun
;
Wang, Weining
;
Lu, Hanqing
收藏
  |  
浏览/下载:270/0
  |  
提交时间:2022/02/16
Image semantic segmentation
Super-resolution semantic segmentation
Relation calibrating
UMAG-Net: A New Unsupervised Multiattention-Guided Network for Hyperspectral and Multispectral Image Fusion
期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2021, 卷号: 14, 页码: 7373-7385
作者:
Liu, Shuaiqi
;
Miao, Siyu
;
Su, Jian
;
Li, Bing
;
Hu, Weiming
;
Zhang, Yu-Dong
收藏
  |  
浏览/下载:220/0
  |  
提交时间:2021/11/02
Tensors
Image fusion
Hyperspectral imaging
Spatial resolution
Feature extraction
Image reconstruction
Dictionaries
Deep learning
hyperspectral images (HSIs)
image fusion
multispectral images (MSIs)
Image Retargetability
期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2020, 卷号: 22, 期号: 3, 页码: 641-654
作者:
Tang, Fan
;
Dong, Weiming
;
Meng, Yiping
;
Ma, Chongyang
;
Wu, Fuzhang
;
Li, Xinrui
;
Lee, Tong-Yee
收藏
  |  
浏览/下载:311/0
  |  
提交时间:2020/06/02
Visualization
Task analysis
Distortion
Measurement
Image resolution
Convolutional neural networks
Semantics
Image retargetability
visual attributes
multi-task learning
deep convolutional neural network