2 papers
cs.LG2026
Data-Efficient Deep Learning: Empirical Guidelines for Training Set Size Estimation in Inertial Sensor Classification
Ofir Kruzel, Itzik Klien
Deep learning models dependency on large-scale inertial datasets presents a significant bottleneck in inertial sensor-based classification tasks, such as human activity recognition…
cs.LG2025
On Neural Inertial Classification Networks for Pedestrian Activity Recognition
Zeev Yampolsky, Ofir Kruzel, Victoria Khalfin Fekson +1
Inertial sensors are crucial for recognizing pedestrian activity. Recent advances in deep learning have greatly improved inertial sensing performance and robustness. Different doma…