Surface defect detection methods for industrial products with imbalanced samples: A review of progress in the 2020s

Author:

Bai DongxuORCID,Li GongfaORCID,Jiang Du,Yun Juntong,Tao Bo,Jiang Guozhang,Sun Ying,Ju Zhaojie

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference206 articles.

1. Dsteelnet: a real-time parallel dilated CNN with atrous spatial pyramid pooling for detecting and classifying defects in surface steel strips;Ahmed;Sensors,2023

2. FDD: a deep learning–based steel defect detectors;Akhyar;Int. J. Adv. Des. Manuf. Technol.,2023

3. An approach towards zero defect manufacturing by combining IIoT data with industrial Social networking;Alexopoulos;Procedia Computer Science,2023

4. An improved PIO feature selection algorithm for IoT network intrusion detection system based on ensemble learning;Alghanam;Expert Syst. Appl.,2023

5. Data augmentation in classification and segmentation: a survey and new strategies;Alomar;Journal of Imaging,2023

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