11 papers
Co-Design of CNN Accelerators for TinyML using Approximate Matrix Decomposition
José Juan Hernández Morales, Georgios Mentzos, Frank Hannig +4
The paradigm shift towards local and on-device inference under stringent resource constraints is represented by the tiny machine learning (TinyML) domain. The primary goal of TinyM…
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,…
Arbitrary Precision Printed Ternary Neural Networks with Holistic Evolutionary Approximation
Vojtech Mrazek, Konstantinos Balaskas, Paula Carolina Lozano Duarte +3
Printed electronics offer a promising alternative for applications beyond silicon-based systems, requiring properties like flexibility, stretchability, conformality, and ultra-low…
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…
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…
Carbon-Efficient 3D DNN Acceleration: Optimizing Performance and Sustainability
Aikaterini Maria Panteleaki, Konstantinos Balaskas, Georgios Zervakis +2
As Deep Neural Networks (DNNs) continue to drive advancements in artificial intelligence, the design of hardware accelerators faces growing concerns over embodied carbon footprint…