跳至主導覽
跳至搜尋
跳過主要內容
國立陽明交通大學研發優勢分析平台 首頁
English
中文
首頁
人員
單位
研究成果
計畫
獎項
活動
貴重儀器
影響
按專業知識、姓名或所屬機構搜尋
Deep learning techniques for the classification of colorectal cancer tissue
Min-Jen Tsai
*
, Yu Han Tao
*
此作品的通信作者
資訊管理研究所
研究成果
:
Article
›
同行評審
52
引文 斯高帕斯(Scopus)
總覽
指紋
指紋
深入研究「Deep learning techniques for the classification of colorectal cancer tissue」主題。共同形成了獨特的指紋。
排序方式
重量
按字母排序
Keyphrases
Deep Learning Methods
100%
Histopathological Images
100%
Colorectal Tissue
100%
Colorectal Cancer
50%
Artificial Intelligence
25%
Clinical Diagnosis
25%
Neural Network
25%
Classification Performance
25%
Network Architecture
25%
Classification Methodology
25%
Network Layer
25%
Objective Evaluation
25%
Text Features
25%
Multiple Tissues
25%
Transfer Learning
25%
Open Dataset
25%
Tissue Characteristics
25%
Deep Learning Technology
25%
Tissue Type
25%
Large Intestine
25%
Performance Learning
25%
External Validation
25%
Characteristic Classification
25%
Intestine Tissue
25%
Organisational Category
25%
CNN Methods
25%
Classifier Transfer
25%
Organizational Types
25%
Computer Science
Deep Learning Technique
100%
Histological Image
100%
Deep Learning Method
66%
Neural Network
33%
Convolutional Neural Network
33%
Classification Performance
33%
Network Architecture
33%
Network Layer
33%
Textual Feature
33%
Learning Technology
33%
Transfer Learning
33%
Histopathological Image
33%
Organisational Type
33%
Artificial Intelligence
33%
Biochemistry, Genetics and Molecular Biology
Transfer of Learning
100%
Large Intestine
100%
Artificial Intelligence
100%
Neuroscience
Neural Network
100%
Earth and Planetary Sciences
Artificial Intelligence
100%