8 September 2022
Electronics | Highly Cited Papers in 2021 in the Section “Artificial Intelligence Circuits and Systems (AICAS)”


The “Artificial Intelligence Circuits and Systems” Section is focused on publications that are related to circuits and systems for artificial intelligence. This Section covers topics of interest within hardware-based deep learning AI and algorithmic deep learning AI using machine learning.

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 2021 listed below:

1. “FPGA Implementation for CNN-Based Optical Remote Sensing Object Detection”
by Ning Zhang et al.
Electronics 2021, 10(3), 282; https://doi.org/10.3390/electronics10030282
Available online: https://www.mdpi.com/2079-9292/10/3/282 

2. “Accelerating Neural Network Inference on FPGA-Based Platforms—A Survey”
by Ran Wu et al.
Electronics 2021, 10(9), 1025; https://doi.org/10.3390/electronics10091025
Available online: https://www.mdpi.com/2079-9292/10/9/1025

3. “FPGA Accelerator for Gradient Boosting Decision Trees”
by Adrián Alcolea et al.
Electronics 2021, 10(3), 314; https://doi.org/10.3390/electronics10030314
Available online: https://www.mdpi.com/2079-9292/10/3/314

4. “A Novel Hybrid Approach Based on Deep CNN to Detect Glaucoma Using Fundus Imaging”
by Rabbia Mahum et al.
Electronics 2021, 11(1), 26; https://doi.org/10.3390/electronics11010026
Available online: https://www.mdpi.com/2079-9292/11/1/26

5. “Design and Implementation of Deep Learning Based Contactless Authentication System Using Hand Gestures”
by Aveen Dayal et al.
Electronics 2021, 10(2), 182; https://doi.org/10.3390/electronics10020182
Available online: https://www.mdpi.com/2079-9292/10/2/182

6. “Forest Fire Smoke Recognition Based on Anchor Box Adaptive Generation Method”
by Enting Zhao et al.
Electronics 2021, 10(5), 566; https://doi.org/10.3390/electronics10050566
Available online: https://www.mdpi.com/2079-9292/10/5/566

7. “Underwater Target Recognition Based on Improved YOLOv4 Neural Network”
by Lingyu Chen et al.
Electronics 2021, 10(14), 1634; https://doi.org/10.3390/electronics10141634
Available online: https://www.mdpi.com/2079-9292/10/14/1634 

8. “Recurrent Neural Network for Human Activity Recognition in Embedded Systems Using PPG and Accelerometer Data”
by Michele Alessandrini et al.
Electronics 2021, 10(14), 1715; https://doi.org/10.3390/electronics10141715
Available online: https://www.mdpi.com/2079-9292/10/14/1715 

9. “Gaining a Sense of Touch Object Stiffness Estimation Using a Soft Gripper and Neural Networks”
by Michal Bednarek et al.
Electronics 2021, 10(1), 96; https://doi.org/10.3390/electronics10010096
Available online: https://www.mdpi.com/2079-9292/10/1/96

10. “Device-Free Crowd Counting Using Multi-Link Wi-Fi CSI Descriptors in Doppler Spectrum”
by Ramon F. Brena et al.
Electronics 2021, 10(3), 315; https://doi.org/10.3390/electronics10030315
Available online: https://www.mdpi.com/2079-9292/10/3/315

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