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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:

DNNs as Applied to Electromagnetics, Antennas, and Propagation—A Review
Andrea Massa, Davide Marcantonio, Xudong Chen, et al.
IEEE Antennas and Wireless Propagation Letters (2019) Vol. 18, Iss. 11, pp. 2225-2229
Closed Access | Times Cited: 205

Showing 1-25 of 205 citing articles:

A REVIEW OF DEEP LEARNING APPROACHES FOR INVERSE SCATTERING PROBLEMS (INVITED REVIEW)
Xudong Chen, Zhun Wei, Maokun Li, et al.
Electromagnetic waves (2020) Vol. 167, pp. 67-81
Open Access | Times Cited: 222
Multi-objective hybrid split-ring resonator and electromagnetic bandgap structure-based fractal antennas using hybrid metaheuristic framework for wireless applications
Satheeshkumar Palanisamy, S Saranya Rubini, Osamah Ibrahim Khalaf, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 18
Deep learning: a new tool for photonic nanostructure design
Ravi S. Hegde
Nanoscale Advances (2020) Vol. 2, Iss. 3, pp. 1007-1023
Open Access | Times Cited: 116
Deep Learning-Based Inversion Methods for Solving Inverse Scattering Problems With Phaseless Data
Kuiwen Xu, Liang Wu, Xiuzhu Ye, et al.
IEEE Transactions on Antennas and Propagation (2020) Vol. 68, Iss. 11, pp. 7457-7470
Closed Access | Times Cited: 94
Noninvasive Inline Food Inspection via Microwave Imaging Technology: An Application Example in the Food Industry
J. A. Tobón Vasquez, Rosa Scapaticci, Giovanna Turvani, et al.
IEEE Antennas and Propagation Magazine (2020) Vol. 62, Iss. 5, pp. 18-32
Closed Access | Times Cited: 72
Nonlinear S-Parameters Inversion for Stroke Imaging
Alessandro Fedeli, Valentina Schenone, Andrea Randazzo, et al.
IEEE Transactions on Microwave Theory and Techniques (2020) Vol. 69, Iss. 3, pp. 1760-1771
Closed Access | Times Cited: 71
Machine Learning for Design Optimization of Electromagnetic Devices: Recent Developments and Future Directions
Yanbin Li, Gang Lei, Gerd Bramerdorfer, et al.
Applied Sciences (2021) Vol. 11, Iss. 4, pp. 1627-1627
Open Access | Times Cited: 65
Artificial Intelligence: New Frontiers in Real-Time Inverse Scattering and Electromagnetic Imaging
Marco Salucci, Manuel Arrebola, Tao Shan, et al.
IEEE Transactions on Antennas and Propagation (2022) Vol. 70, Iss. 8, pp. 6349-6364
Closed Access | Times Cited: 56
Prior-Knowledge-Guided Deep-Learning-Enabled Synthesis for Broadband and Large Phase Shift Range Metacells in Metalens Antenna
Peiqin Liu, Liushifeng Chen, Zhi Ning Chen
IEEE Transactions on Antennas and Propagation (2022) Vol. 70, Iss. 7, pp. 5024-5034
Closed Access | Times Cited: 54
Physics-Embedded Machine Learning for Electromagnetic Data Imaging: Examining three types of data-driven imaging methods
Rui Guo, Tianyao Huang, Maokun Li, et al.
IEEE Signal Processing Magazine (2023) Vol. 40, Iss. 2, pp. 18-31
Closed Access | Times Cited: 36
Emerging Technologies for 6G Communication Networks: Machine Learning Approaches
Annisa Anggun Puspitasari, To Truong An, Mohammed H. Alsharif, et al.
Sensors (2023) Vol. 23, Iss. 18, pp. 7709-7709
Open Access | Times Cited: 26
Learning-Based Fast Electromagnetic Scattering Solver Through Generative Adversarial Network
Zhenchao Ma, Kuiwen Xu, Rencheng Song, et al.
IEEE Transactions on Antennas and Propagation (2020) Vol. 69, Iss. 4, pp. 2194-2208
Closed Access | Times Cited: 66
Uncertainty Quantification in Inverse Scattering Problems With Bayesian Convolutional Neural Networks
Zhun Wei, Xudong Chen
IEEE Transactions on Antennas and Propagation (2020) Vol. 69, Iss. 6, pp. 3409-3418
Open Access | Times Cited: 59
Joint Inversion of Audio-Magnetotelluric and Seismic Travel Time Data With Deep Learning Constraint
Rui Guo, He Ming Yao, Maokun Li, et al.
IEEE Transactions on Geoscience and Remote Sensing (2020) Vol. 59, Iss. 9, pp. 7982-7995
Closed Access | Times Cited: 59
On the Design of Complex EM Devices and Systems Through the System-by-Design Paradigm: A Framework for Dealing With the Computational Complexity
Andrea Massa, Marco Salucci
IEEE Transactions on Antennas and Propagation (2021) Vol. 70, Iss. 2, pp. 1328-1343
Open Access | Times Cited: 52
Full-Range Amplitude–Phase Metacells for Sidelobe Suppression of Metalens Antenna Using Prior-Knowledge-Guided Deep- Learning -Enabled Synthesis
Peiqin Liu, Zhi Ning Chen
IEEE Transactions on Antennas and Propagation (2023) Vol. 71, Iss. 6, pp. 5036-5045
Closed Access | Times Cited: 23
Physics-Informed Supervised Residual Learning for Electromagnetic Modeling
Tao Shan, Jinhong Zeng, Xiaoqian Song, et al.
IEEE Transactions on Antennas and Propagation (2023) Vol. 71, Iss. 4, pp. 3393-3407
Open Access | Times Cited: 21
Improving DOA Estimation via an Optimal Deep Residual Neural Network Classifier on Uniform Linear Arrays
Haya Al Kassir, Nikolaos V. Kantartzis, Pavlos I. Lazaridis, et al.
IEEE Open Journal of Antennas and Propagation (2024) Vol. 5, Iss. 2, pp. 460-473
Open Access | Times Cited: 8
An Improved Deep Learning Scheme for Solving 2-D and 3-D Inverse Scattering Problems
Yulong Zhou, Yu Zhong, Zhun Wei, et al.
IEEE Transactions on Antennas and Propagation (2020) Vol. 69, Iss. 5, pp. 2853-2863
Closed Access | Times Cited: 50
Artificial Intelligence for Adaptive and Reconfigurable Antenna Arrays: A Review
Francesco Zardi, Payam Nayeri, Paolo Rocca, et al.
IEEE Antennas and Propagation Magazine (2020) Vol. 63, Iss. 3, pp. 28-38
Closed Access | Times Cited: 47
Deep Learning-Based Inverse Scattering With Structural Similarity Loss Functions
Youyou Huang, Rencheng Song, Kuiwen Xu, et al.
IEEE Sensors Journal (2020) Vol. 21, Iss. 4, pp. 4900-4907
Closed Access | Times Cited: 46
Predicting Scattering From Complex Nano-Structures via Deep Learning
Yongzhong Li, Yinpeng Wang, Shutong Qi, et al.
IEEE Access (2020) Vol. 8, pp. 139983-139993
Open Access | Times Cited: 45
The Explosion of Artificial Intelligence in Antennas and Propagation: How Deep Learning Is Advancing Our State of the Art
Sawyer D. Campbell, R. Jenkins, Philip O’Connor, et al.
IEEE Antennas and Propagation Magazine (2020) Vol. 63, Iss. 3, pp. 16-27
Closed Access | Times Cited: 41
An Effective Artificial Neural Network-Based Method for Linear Array Beampattern Synthesis
Can Cui, Wen Tao Li, Xiu Tiao Ye, et al.
IEEE Transactions on Antennas and Propagation (2021) Vol. 69, Iss. 10, pp. 6431-6443
Closed Access | Times Cited: 41
Fully Automated Design Method Based on Reinforcement Learning and Surrogate Modeling for Antenna Array Decoupling
Zhaohui Wei, Zhao Zhou, Peng Wang, et al.
IEEE Transactions on Antennas and Propagation (2022) Vol. 71, Iss. 1, pp. 660-671
Open Access | Times Cited: 27
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