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Computational complexity reduction of neural networks of brain tumor image segmentation by introducing fermi–dirac correction functions
Yen Ling Tai, Shin Jhe Huang,
Chien Chang Chen
, Henry Horng Shing Lu
認知智慧與精準健康照護研究中心
生醫科學與工程學系
研究成果
:
雜誌貢獻
›
期刊論文
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同行評審
11
引文 斯高帕斯（Scopus）
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深入研究「Computational complexity reduction of neural networks of brain tumor image segmentation by introducing fermi–dirac correction functions」主題。共同形成了獨特的指紋。
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Keyphrases
Neural Network
100%
MRI Brain Tumor
100%
Tumour Image Segmentation
100%
Computational Complexity Reduction
100%
Correction Function
100%
Preprocessing Techniques
28%
Computation Time
28%
Deep Learning Methods
28%
High Performance
14%
Computational Complexity
14%
Image Segmentation
14%
Band Theory
14%
Normalization Method
14%
High Cost
14%
U-Net
14%
Hardware Architecture
14%
Structural Complexity
14%
Physical Systems
14%
Space Images
14%
Structural Flexibility
14%
Low-cost Hardware
14%
Technical Development
14%
Score Normalization
14%
Gamma Correction
14%
Low Computational
14%
BraTS 2019
14%
Image Augmentation
14%
Non-interaction
14%
Computational Capability
14%
Global Histogram Equalization
14%
Computer Science
Computational Complexity
100%
Image Segmentation
100%
Neural Network
100%
Complexity Reduction
100%
Computational Time
66%
Deep Learning Method
66%
Hardware Cost
33%
Physical System
33%
Hardware Architecture
33%
Histogram Equalization
33%
Score Normalization
33%
Gamma Correction
33%
U-Net
33%
Normalization Function
33%
Computer Hardware
33%
Graphics Processing Unit
33%
Engineering
Computational Complexity
100%
Computational Time
100%
Complexity Reduction
100%
Deep Learning Method
100%
Physical System
50%
Graphics Processing Unit
50%
Histogram
50%
Image Space
50%
Gamma Correction
50%
Material Science
Morphology
100%
Tumor
100%