activity
20232025
most citedBespoke Approximation of Multiplication-Accumulation and Activation Targeting Printed Multilayer Perceptrons

11 citations · 26 across the 10 of their papers we have counts for

collaborators

10 papers

cs.AR2025

Design and Optimization of Mixed-Kernel Mixed-Signal SVMs for Flexible Electronics

Florentia Afentaki, Maha Shatta, Konstantinos Balaskas +3

Flexible Electronics (FE) have emerged as a promising alternative to silicon-based technologies, offering on-demand low-cost fabrication, conformality, and sustainability. However,…

cs.LG2025

Exploration of Low-Power Flexible Stress Monitoring Classifiers for Conformal Wearables

Florentia Afentaki, Sri Sai Rakesh Nakkilla, Konstantinos Balaskas +6

Conventional stress monitoring relies on episodic, symptom-focused interventions, missing the need for continuous, accessible, and cost-efficient solutions. State-of-the-art approa…

cs.AR2025

Support Vector Machines Classification on Bendable RISC-V

Polykarpos Vergos, Theofanis Vergos, Florentia Afentaki +2

Flexible Electronics (FE) technology offers uniquecharacteristics in electronic manufacturing, providing ultra-low-cost, lightweight, and environmentally-friendly alternatives totr…

cs.LG2025

Compact Yet Highly Accurate Printed Classifiers Using Sequential Support Vector Machine Circuits

Ilias Sertaridis, Spyridon Besias, Florentia Afentaki +2

Printed Electronics (PE) technology has emerged as a promising alternative to silicon-based computing. It offers attractive properties such as on-demand ultra-low-cost fabrication,…

cs.LG2025

Late Breaking Results: Energy-Efficient Printed Machine Learning Classifiers with Sequential SVMs

Spyridon Besias, Ilias Sertaridis, Florentia Afentaki +2

Printed Electronics (PE) provide a mechanically flexible and cost-effective solution for machine learning (ML) circuits, compared to silicon-based technologies. However, due to lar…

cs.AR2024

Sequential Printed MLP Circuits for Super TinyML Multi-Sensory Applications

Gurol Saglam, Florentia Afentaki, Georgios Zervakis +1

Super-TinyML aims to optimize machine learning models for deployment on ultra-low-power application domains such as wearable technologies and implants. Such domains also require co…

cs.AR2024★ 2 cited

Reducing ADC Front-end Costs During Training of On-sensor Printed Multilayer Perceptrons

Florentia Afentaki, Paula Carolina Lozano Duarte, Georgios Zervakis +1

Printed electronics technology offers a cost-effectiveand fully-customizable solution to computational needs beyondthe capabilities of traditional silicon technologies, offering ad…

cs.AR2024★ 8 cited

Design and In-training Optimization of Binary Search ADC for Flexible Classifiers

Paula Carolina Lozano Duarte, Florentia Afentaki, Georgios Zervakis +1

Flexible Electronics (FE) offer distinct advantages, including mechanical flexibility and low process temperatures, enabling extremely low-cost production. To address the demands o…

cs.AR2024★ 5 cited

Embedding Hardware Approximations in Discrete Genetic-based Training for Printed MLPs

Florentia Afentaki, Michael Hefenbrock, Georgios Zervakis +1

Printed Electronics (PE) stands out as a promisingtechnology for widespread computing due to its distinct attributes, such as low costs and flexible manufacturing. Unlike tradition…

cs.AR2023★ 11 cited

Bespoke Approximation of Multiplication-Accumulation and Activation Targeting Printed Multilayer Perceptrons

Florentia Afentaki, Gurol Saglam, Argyris Kokkinis +3

Printed Electronics (PE) feature distinct and remarkable characteristics that make them a prominent technology for achieving true ubiquitous computing. This is particularly relevan…