SurfNetv2: An Improved Real-Time SurfNet and Its Applications to Defect Recognition of Calcium Silicate Boards
This paper presents an improved Convolutional Neural Network (CNN) architecture to recognize surface defects of the Calcium Silicate Board (CSB) using visual image information based on a deep learning approach. The proposed CNN architecture is inspired by the existing SurfNet architecture and is nam...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-08-01
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Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/20/16/4356 |