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
Joint supervised and unsupervised deep learning method for single-pixel imaging
Ye Tian,
Ying Fu
*
,
Jun Zhang
*
此作品的通讯作者
计算机学院
信息与电子学院
Beijing Institute of Technology
科研成果
:
期刊稿件
›
文章
›
同行评审
8
引用 （Scopus）
综述
指纹
指纹
探究 'Joint supervised and unsupervised deep learning method for single-pixel imaging' 的科研主题。它们共同构成独一无二的指纹。
分类
加权
按字母排序
Computer Science
Deep Learning
100%
Deep Learning
100%
Image Analysis
66%
Image Quality
66%
Experimental Result
33%
Convolutional Neural Network
33%
Range Dependency
33%
Effective Method
33%
Regularization
33%
Image Reconstruction
33%
Generalization Ability
33%
Network Structures
33%
Superior Performance
33%
Performance Degradation
33%
Total Variation
33%
Change Pattern
33%
Fitting Problem
33%
Engineering
Joints (Structural Components)
100%
Deep Learning
100%
Image Analysis
50%
Demonstrates
25%
Experimental Result
25%
Limitations
25%
Image Reconstruction
25%
Convolutional Neural Network
25%
Real Data
25%
Total Variation
25%
Regularization
25%
Performance Degradation
25%
Image Object
25%
Earth and Planetary Sciences
Imaging Method
100%
State of the Art
50%
Image Reconstruction
50%
Chemical Engineering
Deep Learning
100%
Neural Network
25%