6 papers
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…
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…
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…
Towards efficient keyword spotting using spike-based time difference encoders
Alejandro Pequeño-Zurro, Lyes Khacef, Stefano Panzeri +1
Keyword spotting in edge devices is becoming increasingly important as voice-activated assistants are widely used. However, its deployment is often limited by the extreme low-power…
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…
Low-power event-based face detection with asynchronous neuromorphic hardware
Caterina Caccavella, Federico Paredes-Vallés, Marco Cannici +1
The rise of mobility, IoT and wearables has shifted processing to the edge of the sensors, driven by the need to reduce latency, communication costs and overall energy consumption.…