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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 novel adversarial domain adaptation transfer learning method for tool wear state prediction
Kai Li, Ming-Song Chen, Y.C. Lin, et al.
Knowledge-Based Systems (2022) Vol. 254, pp. 109537-109537
Closed Access | Times Cited: 37

Showing 1-25 of 37 citing articles:

State-of-art, challenges, and outlook on deep hole boring: chatter suppression, tool wear monitoring, and error measurement
Jiefu Sun, Chao Sun, Zheping Yan, et al.
The International Journal of Advanced Manufacturing Technology (2025)
Closed Access | Times Cited: 1
Multi-scan picosecond laser welding of non-optical contact soda lime glass
Xianshi Jia, Kai Li, Zhou Li, et al.
Optics & Laser Technology (2023) Vol. 161, pp. 109164-109164
Closed Access | Times Cited: 38
Integrating physics-informed recurrent Gaussian process regression into instance transfer for predicting tool wear in milling process
Biyao Qiang, Kaining Shi, Ning Liu, et al.
Journal of Manufacturing Systems (2023) Vol. 68, pp. 42-55
Closed Access | Times Cited: 32
Robust Tool Wear Prediction using Multi-Sensor Fusion and Time-Domain Features for the Milling Process using Instance-based Domain Adaptation
Vivek Warke, Satish Kumar, Arunkumar Bongale, et al.
Knowledge-Based Systems (2024) Vol. 288, pp. 111454-111454
Closed Access | Times Cited: 10
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
Decoupled interpretable robust domain generalization networks: A fault diagnosis approach across bearings, working conditions, and artificial-to-real scenarios
Qiu‐Ning Zhu, Hongqi Liu, Chenyu Bao, et al.
Advanced Engineering Informatics (2024) Vol. 61, pp. 102445-102445
Closed Access | Times Cited: 7
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
Multi-sensor signal fusion for tool wear condition monitoring using denoising transformer auto-encoder Resnet
Hui Wang, Shuhui Wang, Weifang Sun, et al.
Journal of Manufacturing Processes (2024) Vol. 124, pp. 1054-1064
Closed Access | Times Cited: 7
Meta-learning-based approach for tool condition monitoring in multi-condition small sample scenarios
Bowen Zhang, Xianli Liu, Caixu Yue, et al.
Mechanical Systems and Signal Processing (2024) Vol. 216, pp. 111444-111444
Closed Access | Times Cited: 6
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
AI-powered trustable and explainable fall detection system using transfer learning
Aryan Nikul Patel, Ramalingam Murugan, Praveen Kumar Reddy Maddikunta, et al.
Image and Vision Computing (2024) Vol. 149, pp. 105164-105164
Closed Access | Times Cited: 5
Multi-task dual-level adversarial transfer learning boosted RUL estimation of CNC milling tools
Pei Wang, Jinrui Liu, Jingshuai Qi, et al.
Knowledge-Based Systems (2025), pp. 113152-113152
Closed Access
A review of artificial intelligence application for machining surface quality prediction: from key factors to model development
Jeong Hoon Ko, Chen Yin
Journal of Intelligent Manufacturing (2025)
Open Access
Process planning of parameter intelligent adjustment for batch machining based on historical data segmented modeling
Juan Lu, Shiying Tu, Ying Li, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 145, pp. 110180-110180
Closed Access
Tool Wear State Identification Method with Variable Cutting Parameters Based on Multi-Source Unsupervised Domain Adaptation
Zhigang Cai, Wangyang Li, Jianxin Song, et al.
Sensors (2025) Vol. 25, Iss. 6, pp. 1742-1742
Open Access
Hierarchical temporal transformer network for tool wear state recognition
Zhongling Xue, Ni Chen, Youling Wu, et al.
Advanced Engineering Informatics (2023) Vol. 58, pp. 102218-102218
Closed Access | Times Cited: 14
Deep learning-based in-situ monitoring of cutting forces in ultra-precision diamond turning
Z. Zha, Pan Guo, Tongke Liu, et al.
Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering (2025)
Closed Access
A domain adversarial graph convolutional network for intelligent monitoring of tool wear in machine tools
Kai Li, Zhou-Long Li, Xianshi Jia, et al.
Computers & Industrial Engineering (2023) Vol. 187, pp. 109795-109795
Closed Access | Times Cited: 10
A tool wear prediction and monitoring method based on machining power signals
Qi Wang, Xi Chen, Qinglong An, et al.
The International Journal of Advanced Manufacturing Technology (2023) Vol. 129, Iss. 11-12, pp. 5387-5401
Open Access | Times Cited: 9
Monitoring of machining process anomalies in diamond turning of Ti6Al4V alloy using transfer learning-based algorithms
K Manjunath, Suman Tewary, Neha Khatri, et al.
Computers & Industrial Engineering (2023) Vol. 182, pp. 109359-109359
Closed Access | Times Cited: 8
Semi-supervised multi-source meta-domain generalization method for tool wear state prediction under varying cutting conditions
Wangyang Li, Hongya Fu, Yue Zhuo, et al.
Journal of Manufacturing Systems (2023) Vol. 71, pp. 323-341
Closed Access | Times Cited: 8
A novel domain adversarial time-varying conditions intervened neural network for drill bit wear monitoring of the jumbo drill under variable working conditions
Lin Lin, Hao Guo, Feng Guo, et al.
Measurement (2023) Vol. 208, pp. 112474-112474
Closed Access | Times Cited: 7
Domain adversarial-based multi-source deep transfer network for cross-production-line time series forecasting
Lei Chen, Chuang Peng, Chen Yang, et al.
Applied Intelligence (2023) Vol. 53, Iss. 19, pp. 22803-22817
Closed Access | Times Cited: 7
An innovative Multisource Lightweight Adaptive Replayed Online Deep Transfer Learning algorithm for tool wear monitoring
Zhilie Gao, Ni Chen, Yinfei Yang, et al.
Journal of Manufacturing Processes (2024) Vol. 124, pp. 261-281
Closed Access | Times Cited: 2
Machining quality prediction of multi-feature parts using integrated multi-source domain dynamic adaptive transfer learning
Pei Wang, Jingshuai Qi, Xun Xu, et al.
Robotics and Computer-Integrated Manufacturing (2024) Vol. 90, pp. 102815-102815
Open Access | Times Cited: 2
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