3 papers
cs.LG2026
Design-Time Optimization of Deep Neural Networks for Intermittent Learning on Microcontrollers
Jakob Schubert, Maximilian Kasper, Maximilian Linke +5
We present a method for designing deep neural networks (DNNs) for intermittent, energy-autonomous, on-device learning on microcontroller units (MCUs). In mobile applications where…
eess.SP2026
Physics-Informed Domain-Invariant Feature Learning with Autoencoder-Driven Gaussian Clustering for Robust Non-line-of-Sight Scenarios
Nisha L. Raichur, Lucas Heublein, Dominik Seuß +2
Jamming and spoofing pose significant threats to wireless and satellite navigation by disrupting radio-frequency (RF) signals and compromising availability and integrity. Robust RF…
cs.AI2026
Pareto Optimal Benchmarking of AI Models on ARM Cortex Processors for Sustainable Embedded Systems
Pranay Jain, Maximilian Kasper, Göran Köber +3
This work presents a practical benchmarking framework for optimizing artificial intelligence (AI) models on ARM Cortex processors (M0+, M4, M7), focusing on energy efficiency, accu…