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西北工业大学 国内
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科研成果
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查看 Scopus 资料
朱 宇
Professor
计算机学院
h-index
1649
引用
19
H-指数
根据储存在 Pure 的刊物以及来自 Scopus 的引用文献数量计算
2009
2025
每年的科研成果
综述
指纹
网络
科研成果
(81)
相似简介
(6)
指纹
深入其中 Yu Zhu 为活跃的研究主题。这些主题标签来自此人的成果。它们共同形成唯一的指纹。
分类
加权
按字母排序
Computer Science
Art Performance
29%
Autoencoder
17%
Blind Image Deblurring
30%
Computer Vision
31%
Convolution Layer
12%
Convolutional Network
10%
Convolutional Neural Network
26%
Correlation Information
10%
de-noising
16%
Deep Learning Method
42%
Deep Neural Network
48%
Depth Estimation
41%
Detection Method
20%
Diffusion Model
30%
Distance Matrix
10%
Domain Feature
13%
Energy Function
10%
Experimental Result
62%
Feature Extraction
18%
Feature Fusion
23%
Feature Space
34%
Frequency Domain
12%
Frequency Information
10%
Generalization Ability
11%
Generative Adversarial Networks
11%
High Dynamic Range Image
52%
High Dynamic Range Imaging
61%
Image Enhancement
20%
image feature
22%
Image Gradient
15%
Image Quality
27%
Image Quality Assessment
25%
Image Restoration
33%
Image Synthesis
27%
Imaging Process
12%
Incremental Approach
10%
Knowledge Distillation
11%
local feature
11%
New-State
15%
Resolution Image
24%
Robust Estimator
10%
Similarity Function
10%
Single-Image Super Resolution
43%
Sparse Representation
15%
Sparsity
11%
Spatial Frequency
10%
super resolution
100%
Synthetic Data
12%
Training Dataset
12%
Visual Quality
16%
Engineering
Aggregation Level
10%
Blurred Image
15%
Bounding Box
13%
Computervision
17%
Convolutional Neural Network
31%
Cost Function
10%
Deconvolution
25%
Deep Learning Method
31%
Degradation Process
10%
Domain Feature
10%
Dynamic Range
35%
Energy Function
10%
Experimental Result
61%
Face Image
15%
Feature Space
19%
Frequency Domain
11%
Gaussian Blur
10%
Group Sparsity
10%
High Resolution
48%
Image Analysis
12%
Image Enhancement
10%
Image Example
10%
Image Quality Assessment
20%
Image Restoration
28%
Image Sequence
13%
Image Synthesis
12%
Internal Feature
10%
Metrics
16%
Motion Blur
15%
Motion Field
10%
Moving Object
10%
Multiscale
47%
Multistage
10%
Objective Evaluation
10%
Past Decade
10%
Pixel Level
11%
Posed Problem
10%
Real Image
10%
Resolution Image
24%
Scale Feature
18%
Segmentation Map
10%
Selection Method
16%
Separability
10%
Single Image
25%
Small-Target Detection
20%
Spatial Frequency
10%
State-of-the-Art Method
17%
Subjective Evaluation
10%
Target Tracking
30%
Tracking (Position)
10%
