DSTEELNet: A Real-Time Parallel Dilated CNN with Atrous Spatial Pyramid Pooling for Detecting and Classifying Defects in Surface Steel Strips

DSTEELNet: A Real-Time Parallel Dilated CNN with Atrous Spatial Pyramid Pooling for Detecting and Classifying Defects in Surface Steel Strips

Automatic defects inspection and classification demonstrate significant importance in improving quality in the steel industry. This paper proposed and developed DSTEELNet convolution neural network (CNN) architecture to improve detection accuracy and the required time to detect defects in surface st...

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Bibliographic Details
Main Author: Khaled R. Ahmed
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Sensors
Subjects:
computer vision
defect detection
defect classification
parallel processing
convolution neural network
Online Access:https://www.mdpi.com/1424-8220/23/1/544

Internet

https://www.mdpi.com/1424-8220/23/1/544

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