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OpenAlex Citation Counts

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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:

Surface roughness prediction through GAN-synthesized power signal as a process signature
Clayton Cooper, Jianjing Zhang, Y. B. Guo, et al.
Journal of Manufacturing Systems (2023) Vol. 68, pp. 660-669
Open Access | Times Cited: 14

Showing 14 citing articles:

Deep learning based multi-source heterogeneous information fusion framework for online monitoring of surface quality in milling process
Xiaofeng Wang, Jihong Yan
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108043-108043
Closed Access | Times Cited: 8
Artificial intelligence in metal forming
Jian Cao, Markus Bambach�, Marion Merklein, et al.
CIRP Annals (2024) Vol. 73, Iss. 2, pp. 561-587
Closed Access | Times Cited: 8
A high-precision and transparent step-wise diagnostic framework for hot-rolled strip crown
Chengyan Ding, Jie Sun, Xiaojian Li, et al.
Journal of Manufacturing Systems (2023) Vol. 71, pp. 144-157
Closed Access | Times Cited: 16
Digital twin enhanced quality prediction method of powder compaction process
Ying Zuo, Hujie You, Xiaofu Zou, et al.
Robotics and Computer-Integrated Manufacturing (2024) Vol. 89, pp. 102762-102762
Closed Access | Times Cited: 5
Prediction of surface roughness using deep learning and data augmentation
Miaoxian Guo, Shouheng Wei, Chentong Han, et al.
Journal of Intelligent Manufacturing and Special Equipment (2024) Vol. 5, Iss. 1, pp. 221-241
Open Access | Times Cited: 4
A generalized generation and evaluation method for cutting process parameter knowledge based on CTGAN
Dan Li, Tianliang Hu, Lili Dong, et al.
Robotics and Computer-Integrated Manufacturing (2025) Vol. 94, pp. 102963-102963
Closed Access
Multi-sensor fusion and machine learning-driven sequence-to-sequence translation for interpretable process signature prediction in machining
Clayton Cooper, Jianjing Zhang, Ihab Ragai, et al.
Journal of Manufacturing Systems (2024) Vol. 75, pp. 288-298
Open Access | Times Cited: 2
Intelligent Recognition of Tool Wear with Artificial Intelligence Agent
Jiaming Gao, Han Qiao, Yilei Zhang
Coatings (2024) Vol. 14, Iss. 7, pp. 827-827
Open Access | Times Cited: 1
Towards AI driven surface roughness evaluation in manufacturing: a prospective study
Sourish Ghosh, Ricardo Knoblauch, Mohamed El Mansori, et al.
Journal of Intelligent Manufacturing (2024)
Open Access | Times Cited: 1
Surface roughness prediction based on fusion of dynamic-static data
Jiayi Wang, Xiaodan Wu, Qian Huang, et al.
Measurement (2024), pp. 116351-116351
Closed Access | Times Cited: 1
Topological Data Analysis in smart manufacturing: State of the art and future directions
Martin Uray, Barbara Giunti, Michael Kerber, et al.
Journal of Manufacturing Systems (2024) Vol. 76, pp. 75-91
Open Access
Prediction of Metal Additively Manufactured Bead Geometry Using Deep Neural Network
Min Seop So, Mohammad Mahruf Mahdi, Duck Bong Kim, et al.
Sensors (2024) Vol. 24, Iss. 19, pp. 6250-6250
Open Access
Surface quality prediction in-situ monitoring system: A deep transfer learning-based regression approach with audible signal
Yaoxuan Zhu, Amir Rashid, Tomas Österlind, et al.
Manufacturing Letters (2024) Vol. 41, pp. 1290-1299
Closed Access
Topological Data Analysis in smart manufacturing processes -- A survey on the state of the art
Martin Uray, Barbara Giunti, Michael Kerber, et al.
arXiv (Cornell University) (2023)
Open Access
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