OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
Application of Generative Adversarial Network and Diverse Feature Extraction Methods to Enhance Classification Accuracy of Tool-Wear Status
Bo-Xiang Chen, Yi‐Chung Chen, Chee-Hoe Loh, et al.
Electronics (2022) Vol. 11, Iss. 15, pp. 2364-2364
Open Access | Times Cited: 8
Bo-Xiang Chen, Yi‐Chung Chen, Chee-Hoe Loh, et al.
Electronics (2022) Vol. 11, Iss. 15, pp. 2364-2364
Open Access | Times Cited: 8
Showing 8 citing articles:
AI for tribology: Present and future
Nian Yin, Pufan Yang, Songkai Liu, et al.
Friction (2024) Vol. 12, Iss. 6, pp. 1060-1097
Open Access | Times Cited: 18
Nian Yin, Pufan Yang, Songkai Liu, et al.
Friction (2024) Vol. 12, Iss. 6, pp. 1060-1097
Open Access | Times Cited: 18
Adaptive weighted generative adversarial network with attention mechanism: A transfer data augmentation method for tool wear prediction
Jianliang He, Yadong Xu, Yi Pan, et al.
Mechanical Systems and Signal Processing (2024) Vol. 212, pp. 111288-111288
Closed Access | Times Cited: 10
Jianliang He, Yadong Xu, Yi Pan, et al.
Mechanical Systems and Signal Processing (2024) Vol. 212, pp. 111288-111288
Closed Access | Times Cited: 10
Hybrid Data Augmentation Combining Screening-Based MCGAN and Manual Transformation for Few-Shot Tool Wear State Recognition
Yu Quan, Changfu Liu, Zhuang Yuan, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 8, pp. 12186-12196
Closed Access | Times Cited: 4
Yu Quan, Changfu Liu, Zhuang Yuan, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 8, pp. 12186-12196
Closed Access | Times Cited: 4
Towards Sustainable Machining: Synthetic Data Generation for Efficient Optical Tool Wear Monitoring via Generative Adversarial Networks
Markus Friedrich, Engjëll Ahmeti, Jonas Dumler, et al.
Lecture notes in mechanical engineering (2025), pp. 544-552
Closed Access
Markus Friedrich, Engjëll Ahmeti, Jonas Dumler, et al.
Lecture notes in mechanical engineering (2025), pp. 544-552
Closed Access
Identification of Tool-Wear State Using Information Fusion and SSA–BP Neural Network
Zishuo Wang, Hongwei Cui, Shuning Liang, et al.
Machines (2025) Vol. 13, Iss. 4, pp. 256-256
Open Access
Zishuo Wang, Hongwei Cui, Shuning Liang, et al.
Machines (2025) Vol. 13, Iss. 4, pp. 256-256
Open Access
A GAN-Based Multi-Sensor Data Augmentation Technique for CNC Machine Tool Wear Prediction
Yuechi Jiang, Benny Drescher, Guoguang Yuan
IEEE Access (2023) Vol. 11, pp. 95782-95795
Open Access | Times Cited: 9
Yuechi Jiang, Benny Drescher, Guoguang Yuan
IEEE Access (2023) Vol. 11, pp. 95782-95795
Open Access | Times Cited: 9
Advances of Future IoE Wireless Network Technology
Gwo-Jiun Horng
Electronics (2023) Vol. 12, Iss. 10, pp. 2164-2164
Open Access | Times Cited: 2
Gwo-Jiun Horng
Electronics (2023) Vol. 12, Iss. 10, pp. 2164-2164
Open Access | Times Cited: 2
Tool wear state recognition for variable sensor combinations by deep forest with parameter adaptive fine-tuning
Xuejun Wang, Ning Li, Dengsheng Lu, et al.
Applied Soft Computing (2024), pp. 112629-112629
Closed Access
Xuejun Wang, Ning Li, Dengsheng Lu, et al.
Applied Soft Computing (2024), pp. 112629-112629
Closed Access
