跳到主要导航
跳到搜索
跳到主要内容
北京理工大学 首页
English
中文
首页
师资队伍
研究单位
科研成果
奖项
按专业知识、名称或附属进行搜索
查看 Scopus 资料
胡 润泽
信息与电子学院
h-index
285
引用
9
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
2018
2025
每年的科研成果
概览
指纹图谱
合作网络
科研成果
(36)
相似学者
(3)
指纹图谱
深入其中 Runze Hu 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
Artificial Neural Network
10%
Attention (Machine Learning)
14%
Captured Image
16%
Computational Cost
21%
Constraint Network
10%
Content Information
10%
Deep Learning
17%
Deep Neural Network
8%
Domain Knowledge
10%
Experimental Result
10%
Extracted Feature
13%
Feature Extraction
10%
Feature Interaction
10%
Feature Selection
13%
finite difference time domain
10%
Finite-Difference Time-Domain (FDTD)
21%
Frequency Domain
10%
Frequency Information
10%
Global Context
10%
Global Feature
11%
Higher Semantic Level
11%
Image Enhancement
10%
Image Fusion
10%
Image Quality
54%
Image Quality Assessment
100%
Image Translation
10%
Interaction Task
10%
Intermediate Frame
10%
Knowledge Distillation
43%
Level Description
10%
local feature
8%
Modulation Method
10%
Neural Network
10%
Noise Sensitivity
10%
Object Detection
10%
Object Detector
10%
Perceptual Capability
10%
Perceptual Quality
10%
Picture Quality
10%
Quality Assessment
21%
Range Dependency
10%
Recognition Algorithm
10%
Reference Image
34%
Regression Method
8%
Ridge Regression
10%
Segmentation Method
10%
Semisupervised Learning
10%
Superior Performance
11%
Target Recognition
21%
Visual Language
10%
Engineering
Acoustic Field
8%
Artificial Neural Network
21%
Assessment Method
10%
Attention-Deficit Hyperactivity Disorder
10%
Computational Cost
22%
Computational Resource
10%
Computer Aided Design
10%
Computer Simulation
24%
Conventional Method
8%
Deep Learning
14%
Deep Learning Method
10%
Deep Neural Network
5%
Defect Detection
21%
Defects
10%
Direction-of-Arrival Estimation
10%
Domain Knowledge
10%
Evaluator
10%
Experimental Result
11%
Frequency Domain
10%
Gaussians
10%
Image Distortion
5%
Image Enhancement
10%
Image Quality Assessment
57%
Image Restoration
5%
Image Translation
10%
Input Sample
7%
Level Semantics
8%
Loss Function
5%
Metrics
11%
Mobile Phone
10%
Model Parameter
14%
Nonlinear System
10%
Normal Modes
10%
Parameter Uncertainty
10%
Perceptual Quality
10%
Prediction Performance
8%
Processing Method
8%
Product Quality
6%
Quality Assessment
21%
Reference Image
10%
Segmenter
10%
Stochastic System
5%
Storage Size
5%
Surface Defect
10%
Surrogate Model
15%
Target Recognition
21%
Tasks
33%
Time Domain
18%
Toeplitz Matrix
10%
Uncertainty Quantification
51%
