collaborators

5 papers

cs.NE2026

Privacy-preserving fall detection at the edge using Sony IMX636 event-based vision sensor and Intel Loihi 2 neuromorphic processor

Lyes Khacef, Philipp Weidel, Susumu Hogyoku +8

Fall detection for elderly care using non-invasive vision-based systems remains an important yet unsolved problem. Driven by strict privacy requirements, inference must run at the…

cs.NE2025

TDE-3: An improved prior for optical flow computation in spiking neural networks

Matthew Yedutenko, Federico Paredes-Valles, Lyes Khacef +1

Motion detection is a primary task required for robotic systems to perceive and navigate in their environment. Proposed in the literature bioinspired neuromorphic Time-Difference E…

cs.RO2025

RGB-Event Fusion with Self-Attention for Collision Prediction

Pietro Bonazzi, Christian Vogt, Michael Jost +4

Ensuring robust and real-time obstacle avoidance is critical for the safe operation of autonomous robots in dynamic, real-world environments. This paper proposes a neural network f…

cs.CV2025

Towards Low-Latency Event-based Obstacle Avoidance on a FPGA-Drone

Pietro Bonazzi, Christian Vogt, Michael Jost +3

This work quantitatively evaluates the performance of event-based vision systems (EVS) against conventional RGB-based models for action prediction in collision avoidance on an FPGA…

cs.DC2025

Contemplating a Lightweight Communication Interface for Asynchronous Many-Task Systems

Jiakun Yan, Marc Snir

Asynchronous Many-Task Systems (AMTs) exhibit different communication patterns from traditional High-Performance Computing (HPC) applications, characterized by asynchrony, concurre…