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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:

A review on deep learning in machining and tool monitoring: methods, opportunities, and challenges
Vahid Nasir, Farrokh Sassani
The International Journal of Advanced Manufacturing Technology (2021) Vol. 115, Iss. 9-10, pp. 2683-2709
Closed Access | Times Cited: 201

Showing 26-50 of 201 citing articles:

Deep Learning and Computer Vision Techniques for Enhanced Quality Control in Manufacturing Processes
Md Raisul Islam, Md Zakir Hossain Zamil, Md. Eshmam Rayed, et al.
IEEE Access (2024) Vol. 12, pp. 121449-121479
Open Access | Times Cited: 8
Cutting tool prognostics enabled by hybrid CNN-LSTM with transfer learning
Mohamed Marei, Weidong Li
The International Journal of Advanced Manufacturing Technology (2021) Vol. 118, Iss. 3-4, pp. 817-836
Closed Access | Times Cited: 51
Transfer learning for spatio-temporal transferability of real-time crash prediction models
Cheuk Ki Man, Mohammed Quddus, Athanasios Theofilatos
Accident Analysis & Prevention (2021) Vol. 165, pp. 106511-106511
Closed Access | Times Cited: 47
Infrastructure monitoring and quality diagnosis in CNC machining: A review
Myrsini Ntemi, Spyridon Paraschos, Αναστάσιος Καρακώστας, et al.
CIRP journal of manufacturing science and technology (2022) Vol. 38, pp. 631-649
Open Access | Times Cited: 31
A Review on AI for Smart Manufacturing: Deep Learning Challenges and Solutions
Jiawen Xu, Matthias Kovatsch, Denny Mattern, et al.
Applied Sciences (2022) Vol. 12, Iss. 16, pp. 8239-8239
Open Access | Times Cited: 31
A Real Time Arabic Sign Language Alphabets (ArSLA) Recognition Model Using Deep Learning Architecture
Zaran Alsaadi, Easa Alshamani, Mohammed Alrehaili, et al.
Computers (2022) Vol. 11, Iss. 5, pp. 78-78
Open Access | Times Cited: 29
Fault detection and diagnosis of air brake system: A systematic review
Zhe-Fan Hou, C.K.M. Lee, Yaqiong Lv, et al.
Journal of Manufacturing Systems (2023) Vol. 71, pp. 34-58
Closed Access | Times Cited: 17
Toward practical tool wear prediction paradigm with optimized regressive Siamese neural network
Jian Duan, Jianqiang Liang, Xinjia Yu, et al.
Advanced Engineering Informatics (2023) Vol. 58, pp. 102200-102200
Closed Access | Times Cited: 17
Cross-domain tool wear condition monitoring via residual attention hybrid adaptation network
Zhiwen Huang, Weidong Li, Jianmin Zhu, et al.
Journal of Manufacturing Systems (2023) Vol. 72, pp. 406-423
Closed Access | Times Cited: 17
Artificial Intelligence Methods for the Construction and Management of Buildings
Светлана Иванова, Aleksandr Kuznetsov, Roman Zverev, et al.
Sensors (2023) Vol. 23, Iss. 21, pp. 8740-8740
Open Access | Times Cited: 16
Deploying deep convolutional neural network to the battle against cancer: Towards flexible healthcare systems
Mohammad Shahin, F. Frank Chen, Ali Hosseinzadeh, et al.
Informatics in Medicine Unlocked (2024) Vol. 47, pp. 101494-101494
Open Access | Times Cited: 6
Novel Framework for Quality Control in Vibration Monitoring of CNC Machining
Georgia Apostolou, Myrsini Ntemi, Spyridon Paraschos, et al.
Sensors (2024) Vol. 24, Iss. 1, pp. 307-307
Open Access | Times Cited: 5
A novel method based on deep transfer learning for tool wear state prediction under cross-dataset
Yifan Wang, Jie Gao, Wei Wang, et al.
The International Journal of Advanced Manufacturing Technology (2024) Vol. 131, Iss. 1, pp. 171-182
Closed Access | Times Cited: 5
Custom Loss Functions in XGBoost Algorithm for Enhanced Critical Error Mitigation in Drill-Wear Analysis of Melamine-Faced Chipboard
Michał Bukowski, Jarosław Kurek, Bartosz Świderski, et al.
Sensors (2024) Vol. 24, Iss. 4, pp. 1092-1092
Open Access | Times Cited: 5
Model-data hybrid driven approach for remaining useful life prediction of cutting tool based on improved inverse Gaussian process
Ning Zhang, Zhanpeng Jiang, Yingbing Sun, et al.
Journal of Manufacturing Processes (2024) Vol. 124, pp. 604-620
Closed Access | Times Cited: 5
Machine-Learning- and Internet-of-Things-Driven Techniques for Monitoring Tool Wear in Machining Process: A Comprehensive Review
Sudhan Kasiviswanathan, G. Sakthivel, T. Mohanraj, et al.
Journal of Sensor and Actuator Networks (2024) Vol. 13, Iss. 5, pp. 53-53
Open Access | Times Cited: 5
Artificial Intelligence and Machine Learning in Tribology: Selected Case Studies and Overall Potential
Raj Shah, Rudy Jaramillo, Garvin Thomas, et al.
Advanced Engineering Materials (2025)
Closed Access
A Spatial–Temporal Adaptive Graph Convolutional Network with Multi-Sensor Signals for Tool Wear Prediction
Yu Xia, Guangji Zheng, Ye Li, et al.
Applied Sciences (2025) Vol. 15, Iss. 4, pp. 2058-2058
Open Access
Acoustic Emission
Voichiţa Bucur
Springer eBooks (2025), pp. 527-626
Closed Access
Using deep convolutional networks combined with signal processing techniques for accurate prediction of surface quality
M Zangane, Mahya Shahbazi, Seyed Ali Niknam
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Advances in Acoustic Emission Monitoring for Grinding of Hard and Brittle Materials
Zhiqi Fan, Chengwei Kang, Xuliang Li, et al.
Journal of Materials Research and Technology (2025)
Open Access
Technology development and commercial applications of industrial fault diagnosis system: a review
Chengze Liu, A. Cichoń, Grzegorz Królczyk, et al.
The International Journal of Advanced Manufacturing Technology (2021) Vol. 118, Iss. 11-12, pp. 3497-3529
Open Access | Times Cited: 35
Prediction of milling force based on spindle current signal by neural networks
Defeng Peng, Hongkun Li, Yuebang Dai, et al.
Measurement (2022) Vol. 205, pp. 112153-112153
Closed Access | Times Cited: 22
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
An Intelligent Multiscale Spatiotemporal Fusion Network Model for TCM
Yu Quan, Changfu Liu, Zhuang Yuan, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 7, pp. 6628-6637
Closed Access | Times Cited: 13

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