What is it about?
The paper is about using advanced deep learning algorithms to solve problems in the manufacturing field, specifically identifying steel surface defects. We propose a deep learning model that uses an ensemble of two pre-trained Convolutional Neural Networks to classify six common steel strip surface defects.
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Why is it important?
Identifying steel surface defects is a crucial task in the steel industry, and the proposed deep learning-based approach offers an accurate, efficient, and reliable solution. Accurately detecting steel surface defects helps ensure the quality of the final product and reduces the risk of failure or malfunction in the end-use applications.
Read the Original
This page is a summary of: Deep Ensemble Transfer Learning-based Approach for Classifying Hot-Rolled Steel Strips Surface Defects, November 2022, Research Square,
DOI: 10.21203/rs.3.rs-2235865/v1.
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