7 citations · 7 across the 5 of their papers we have counts for
9 papers
Hardware-aware Graph Neural Networks prunning for embedded event-based vision
Piotr Wzorek, Kamil Jeziorek, Tomasz Kryjak
Event-based cameras are gaining popularity as the sensor of choice for mobile robotics, due to their high performance in dynamic environments. However, these applications require e…
Event Detection in Videos: A Framework for the Development of New Methods
Anastasia Zakharova, Thierry Bouwmans, Anthony Cioppa +13
Event detection tasks in videos, the most important aspect of video surveillance, aim to detect events either at the pixel-level, frame-level, or clip-level. Plenty of methods inte…
Embedded Graph Convolutional Networks for Real-Time Event Data Processing on SoC FPGAs
Kamil Jeziorek, Piotr Wzorek, Krzysztof Blachut +2
The utilisation of event cameras represents an important and swiftly evolving trend aimed at addressing the constraints of traditional video systems. Particularly within the automo…
End-to-End Keyword Spotting on FPGA Using Graph Neural Networks with a Neuromorphic Auditory Sensor
Wiktor Matykiewicz, Piotr Wzorek, Kamil Jeziorek +4
With the rapid growth of mobile robotics and embedded intelligence, there is an increasing demand for efficient on-device data processing on edge platforms. A promising research di…
Hardware-accelerated graph neural networks: an alternative approach for neuromorphic event-based audio classification and keyword spotting on SoC FPGA
Kamil Jeziorek, Piotr Wzorek, Krzysztof Blachut +6
As the volume of data recorded by embedded edge sensors increases, particularly from neuromorphic devices producing discrete event streams, there is a growing need for hardware-awa…
Learning from Noise: Enhancing DNNs for Event-Based Vision through Controlled Noise Injection
Marcin Kowalczyk, Kamil Jeziorek, Tomasz Kryjak
Event-based sensors offer significant advantages over traditional frame-based cameras, especially in scenarios involving rapid motion or challenging lighting conditions. However, e…