Article Versions Notes

Chen B-X, Chen Y-C, Loh C-H, Chou Y-C, Wang F-C, Su C-T. Application of Generative Adversarial Network and Diverse Feature Extraction Methods to Enhance Classification Accuracy of Tool-Wear Status. Electronics. 2022; 11(15):2364. https://doi.org/10.3390/electronics11152364

Chen, Bo-Xiang, Yi-Chung Chen, Chee-Hoe Loh, Ying-Chun Chou, Fu-Cheng Wang, and Chwen-Tzeng Su. 2022. "Application of Generative Adversarial Network and Diverse Feature Extraction Methods to Enhance Classification Accuracy of Tool-Wear Status" Electronics 11, no. 15: 2364. https://doi.org/10.3390/electronics11152364

Chen, B.-X., Chen, Y.-C., Loh, C.-H., Chou, Y.-C., Wang, F.-C., & Su, C.-T. (2022). Application of Generative Adversarial Network and Diverse Feature Extraction Methods to Enhance Classification Accuracy of Tool-Wear Status. Electronics, 11(15), 2364. https://doi.org/10.3390/electronics11152364