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A beneficial dual transformation approach for deep learning networks used in steel surface defect detection
Fityanul Akhyar,
Chih Yang Lin
, Gugan S. Kathiresan
機械工程學系
研究成果
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引文 斯高帕斯（Scopus）
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Keyphrases
Transformation Approach
100%
Deep Learning Network
100%
Dual Transformation
100%
Steel Surface Defect Detection
100%
Object Detection
50%
Feature Map
50%
Training Image
50%
Deep Learning Methods
50%
Data Augmentation
50%
Challenging Tasks
50%
Color Distribution
50%
Art Objects
50%
Object Detection Algorithm
50%
Bilinear Interpolation
50%
Defect Detection System
50%
Severstal
50%
Steel Surface Defects
50%
Tiny Size
50%
High-resolution Network
50%
HSV Color Model
50%
Small Resolution
50%
Computer Science
Object Detection
100%
Deep Learning Method
100%
Experimental Result
50%
And-States
50%
Training Image
50%
Data Augmentation
50%
Color Distribution
50%
Bilinear Interpolation
50%
Feature Map
50%
Engineering
Defect Detection
100%
Steel Surface
100%
Deep Learning Method
100%
Surface Defect
100%
Experimental Result
33%
High Resolution
33%
Bilinear Interpolation
33%
Chemical Engineering
Deep Learning Method
100%
Material Science
Surface Defect
100%