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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:

Vega: A Ten-Core SoC for IoT Endnodes With DNN Acceleration and Cognitive Wake-Up From MRAM-Based State-Retentive Sleep Mode
Davide Rossi, Francesco Conti, Manuel Eggimann, et al.
IEEE Journal of Solid-State Circuits (2021) Vol. 57, Iss. 1, pp. 127-139
Open Access | Times Cited: 66

Showing 1-25 of 66 citing articles:

An Ultra-Low Power TinyML System for Real-Time Visual Processing at Edge
Kunran Xu, Huawei Zhang, Yishi Li, et al.
IEEE Transactions on Circuits & Systems II Express Briefs (2023) Vol. 70, Iss. 7, pp. 2640-2644
Open Access | Times Cited: 22
A Heterogeneous In-Memory Computing Cluster for Flexible End-to-End Inference of Real-World Deep Neural Networks
Angelo Garofalo, Gianmarco Ottavi, Francesco Conti, et al.
IEEE Journal on Emerging and Selected Topics in Circuits and Systems (2022) Vol. 12, Iss. 2, pp. 422-435
Open Access | Times Cited: 28
TinyVers: A Tiny Versatile System-on-Chip With State-Retentive eMRAM for ML Inference at the Extreme Edge
Vikram Jain, Sebastian Giraldo, Jaro De Roose, et al.
IEEE Journal of Solid-State Circuits (2023) Vol. 58, Iss. 8, pp. 2360-2371
Open Access | Times Cited: 21
Minimizing artifact-induced false-alarms for seizure detection in wearable EEG devices with gradient-boosted tree classifiers
Thorir Mar Ingolfsson, Simone Benatti, Xiaying Wang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
Day–Night architecture: Development of an ultra-low power RISC-V processor for wearable anomaly detection
Eun‐Jin Choi, Jina Park, Kyeongwon Lee, et al.
Journal of Systems Architecture (2024) Vol. 152, pp. 103161-103161
Open Access | Times Cited: 6
Optimizing BFloat16 Deployment of Tiny Transformers on Ultra-Low Power Extreme Edge SoCs
Alberto Dequino, Luca Bompani, Luca Benini, et al.
Journal of Low Power Electronics and Applications (2025) Vol. 15, Iss. 1, pp. 8-8
Open Access
Dustin: A 16-Cores Parallel Ultra-Low-Power Cluster With 2b-to-32b Fully Flexible Bit-Precision and Vector Lockstep Execution Mode
Gianmarco Ottavi, Angelo Garofalo, Giuseppe Tagliavini, et al.
IEEE Transactions on Circuits and Systems I Regular Papers (2023) Vol. 70, Iss. 6, pp. 2450-2463
Open Access | Times Cited: 12
HULK-V: a Heterogeneous Ultra-low-power Linux capable RISC-V SoC
Luca Valente, Yvan Tortorella, M. Sinigaglia, et al.
Design, Automation & Test in Europe Conference & Exhibition (DATE), 2015 (2023), pp. 1-6
Open Access | Times Cited: 12
A Survey on Deep Learning Hardware Accelerators for Heterogeneous HPC Platforms
Cristina Silvano, Daniele Ielmini, Fabrizio Ferrandi, et al.
ACM Computing Surveys (2025)
Open Access
Kraken: A Direct Event/Frame-Based Multi-sensor Fusion SoC for Ultra-Efficient Visual Processing in Nano-UAVs
Alfio Di Mauro, Moritz Scherer, Davide Rossi, et al.
(2022), pp. 1-19
Open Access | Times Cited: 18
A Survey of MRAM-Centric Computing: From Near Memory to In Memory
Yueting Li, Tianshuo Bai, Xinyi Xu, et al.
IEEE Transactions on Emerging Topics in Computing (2022) Vol. 11, Iss. 2, pp. 318-330
Closed Access | Times Cited: 17
Reduced precision floating-point optimization for Deep Neural Network On-Device Learning on microcontrollers
Davide Nadalini, Manuele Rusci, Luca Benini, et al.
Future Generation Computer Systems (2023) Vol. 149, pp. 212-226
Open Access | Times Cited: 10
Directly-trained Spiking Neural Networks for Deep Reinforcement Learning: Energy efficient implementation of event-based obstacle avoidance on a neuromorphic accelerator
Luca Zanatta, Alfio Di Mauro, Francesco Barchi, et al.
Neurocomputing (2023) Vol. 562, pp. 126885-126885
Open Access | Times Cited: 9
NanoSLAM: Enabling Fully Onboard SLAM for Tiny Robots
Vlad Niculescu, Tommaso Polonelli, Michele Magno, et al.
IEEE Internet of Things Journal (2023) Vol. 11, Iss. 8, pp. 13584-13607
Open Access | Times Cited: 9
Flexible and Fully Quantized Lightweight TinyissimoYOLO for Ultra-Low-Power Edge Systems
Julian Moosmann, Hanna Müller, Nicky Zimmerman, et al.
IEEE Access (2024) Vol. 12, pp. 75093-75107
Open Access | Times Cited: 3
Voice Activated IoT Devices for Healthcare: Design Challenges and Emerging Applications
Petros Spachos, Stefano Gregori, M. Jamal Deen
IEEE Transactions on Circuits & Systems II Express Briefs (2022) Vol. 69, Iss. 7, pp. 3101-3107
Closed Access | Times Cited: 14
Cheshire: A Lightweight, Linux-Capable RISC-V Host Platform for Domain-Specific Accelerator Plug-In
Alessandro Ottaviano, Thomas Benz, Paul Scheffler, et al.
IEEE Transactions on Circuits & Systems II Express Briefs (2023) Vol. 70, Iss. 10, pp. 3777-3781
Open Access | Times Cited: 8
Marsellus: A Heterogeneous RISC-V AI-IoT End-Node SoC With 2–8 b DNN Acceleration and 30%-Boost Adaptive Body Biasing
Francesco Conti, Gianna Paulin, Angelo Garofalo, et al.
IEEE Journal of Solid-State Circuits (2023) Vol. 59, Iss. 1, pp. 128-142
Open Access | Times Cited: 8
Development of a Low-Power Touch-Based Lifelogging Processor
Hyeonguk Jang, Sukho Lee, Hyungil Park, et al.
IEEE Transactions on Circuits & Systems II Express Briefs (2024) Vol. 71, Iss. 8, pp. 3910-3914
Closed Access | Times Cited: 2
Siracusa: A 16 nm Heterogenous RISC-V SoC for Extended Reality With At-MRAM Neural Engine
Arpan Suravi Prasad, Moritz Scherer, Francesco Conti, et al.
IEEE Journal of Solid-State Circuits (2024) Vol. 59, Iss. 7, pp. 2055-2069
Open Access | Times Cited: 2
Roadmap on low-power electronics
R. Ramesh, Sayeef Salahuddin, Suman Datta, et al.
APL Materials (2024) Vol. 12, Iss. 9
Open Access | Times Cited: 2
PULP-TrainLib: Enabling On-Device Training for RISC-V Multi-core MCUs Through Performance-Driven Autotuning
Davide Nadalini, Manuele Rusci, Giuseppe Tagliavini, et al.
Lecture notes in computer science (2022), pp. 200-216
Closed Access | Times Cited: 11
DARKSIDE: A Heterogeneous RISC-V Compute Cluster for Extreme-Edge On-Chip DNN Inference and Training
Angelo Garofalo, Yvan Tortorella, Matteo Perotti, et al.
IEEE Open Journal of the Solid-State Circuits Society (2022) Vol. 2, pp. 231-243
Open Access | Times Cited: 11
A Systolic Neural CPU Processor Combining Deep Learning and General-Purpose Computing With Enhanced Data Locality and End-to-End Performance
Yuhao Ju, Jie Gu
IEEE Journal of Solid-State Circuits (2022) Vol. 58, Iss. 1, pp. 216-226
Closed Access | Times Cited: 11
Fully On-board Low-Power Localization with Multizone Time-of-Flight Sensors on Nano-UAVs
Hanna Müller, Nicky Zimmerman, Tommaso Polonelli, et al.
Design, Automation & Test in Europe Conference & Exhibition (DATE), 2015 (2023)
Open Access | Times Cited: 6
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