Electronics | Highly Cited Papers in 2024 in the Section “Computer Science & Engineering”

The primary focus of the “Computer Science & Engineering” Section is the field of advanced computer science and engineering. It presents high-quality papers that address state-of-the-art technology, including Deep Tech, Edge Computing, Fog Computing, Artificial Intelligence, Machine Learning, Deep Learning, Emotional Systems, Fintech, Blockchain, IoT, Industry 4.0, Smart Cities, Smart Grids, Intelligent Textiles, Distributed Computing, as well as other chief technologies in this field.

As they are of an open access format, you have free and unlimited access to the full text of all the articles published in our journal. We welcome you to read our most highly cited papers published in 2024 below:

“Exhaustive Study into Machine Learning and Deep Learning Methods for Multilingual Cyberbullying Detection in Bangla and Chittagonian Texts”
by Tanjim Mahmud, Michal Ptaszynski and Fumito Masui
Electronics 2024, 13(9), 1677; https://doi.org/10.3390/electronics13091677
Full text available online: https://www.mdpi.com/2079-9292/13/9/1677

“The Challenges of Machine Learning: A Critical Review”
by Enrico Barbierato and Alice Gatti
Electronics 2024, 13(2), 416; https://doi.org/10.3390/electronics13020416
Full text available online: https://www.mdpi.com/2079-9292/13/2/416

“A Resource-Based Dynamic Pricing and Forced Forwarding Incentive Algorithm in Socially Aware Networking”
by Xuemin Zhang, Yuan Li, Zenggang Xiong, Yanchao Liu, Shihui Wang and Delin Hou
Electronics 2024, 13(15), 3044; https://doi.org/10.3390/electronics13153044
Full text available online: https://www.mdpi.com/2079-9292/13/15/3044

“Lightweight Privacy Protection via Adversarial Sample”
by Guangxu Xie, Gaopan Hou, Qingqi Pei and Haibo Huang
Electronics 2024, 13(7), 1230; https://doi.org/10.3390/electronics13071230
Full text available online: https://www.mdpi.com/2079-9292/13/7/1230

“Deep Learning in the Phase Extraction of Electronic Speckle Pattern Interferometry”
by Wenbo Jiang, Tong Ren and Qianhua Fu
Electronics 2024, 13(2), 418; https://doi.org/10.3390/electronics13020418
Full text available online: https://www.mdpi.com/2079-9292/13/2/418

“A Systematic Review of Synthetic Data Generation Techniques Using Generative AI”
by Mandeep Goyal and Qusay H. Mahmoud
Electronics 2024, 13(17), 3509; https://doi.org/10.3390/electronics13173509
Full text available online: https://www.mdpi.com/2079-9292/13/17/3509

“Artificial Intelligence-Based Algorithms in Medical Image Scan Segmentation and Intelligent Visual Content Generation-A Concise Overview”
Zofia Rudnicka, Janusz Szczepanski and Agnieszka Pregowska
Electronics 2024, 13(4), 746; https://doi.org/10.3390/electronics13040746
Full text available online: https://www.mdpi.com/2079-9292/13/4/746

“Cardiac Healthcare Digital Twins Supported by Artificial Intelligence-Based Algorithms and Extended Reality—A Systematic Review”
by Zofia Rudnicka, Klaudia Proniewska, Mark Perkins and Agnieszka Pregowska
Electronics 2024, 13(5), 866; https://doi.org/10.3390/electronics13050866
Full text available online: https://www.mdpi.com/2079-9292/13/5/866

“A Survey of Intelligent End-to-End Networking Solutions: Integrating Graph Neural Networks and Deep Reinforcement Learning Approaches”
by Prohim Tam, Seyha Ros, Inseok Song, Seungwoo Kang and Seokhoon Kim
Electronics 2024, 13(5), 994; https://doi.org/10.3390/electronics13050994
Full text available online: https://www.mdpi.com/2079-9292/13/5/994

“Using Ensemble Learning for Anomaly Detection in Cyber-Physical Systems”
by Nicholas Jeffrey, Qing Tan and José R. Villar
Electronics 2024, 13(7), 1391; https://doi.org/10.3390/electronics13071391
Full text available online: https://www.mdpi.com/2079-9292/13/7/1391