activity
20212026
most citedTraffic Sign Detection With Event Cameras and DCNN

11 citations · 29 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2026

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…

cs.LG2026

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…

cs.LG2026

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…

cs.LG2025★ 3 cited

Hardware-Accelerated Event-Graph Neural Networks for Low-Latency Time-Series Classification on SoC FPGA

Hiroshi Nakano, Krzysztof Blachut, Kamil Jeziorek +6

As the quantities of data recorded by embedded edge sensors grow, so too does the need for intelligent local processing. Such data often comes in the form of time-series signals, b…

cs.CV2024

Increasing the scalability of graph convolution for FPGA-implemented event-based vision

Piotr Wzorek, Kamil Jeziorek, Tomasz Kryjak +1

Event cameras are becoming increasingly popular as an alternative to traditional frame-based vision sensors, especially in mobile robotics. Taking full advantage of their high temp…

cs.CV2024★ 8 cited

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…

cs.CV2024★ 5 cited

Optimising Graph Representation for Hardware Implementation of Graph Convolutional Networks for Event-based Vision

Kamil Jeziorek, Piotr Wzorek, Krzysztof Blachut +2

Event-based vision is an emerging research field involving processing data generated by Dynamic Vision Sensors (neuromorphic cameras). One of the latest proposals in this area are…

cs.CV2023

Pedestrian detection with high-resolution event camera

Piotr Wzorek, Tomasz Kryjak

Despite the dynamic development of computer vision algorithms, the implementation of perception and control systems for autonomous vehicles such as drones and self-driving cars sti…

cs.CV2022★ 11 cited

Traffic Sign Detection With Event Cameras and DCNN

Piotr Wzorek, Tomasz Kryjak

In recent years, event cameras (DVS - Dynamic Vision Sensors) have been used in vision systems as an alternative or supplement to traditional cameras. They are characterised by hig…

cs.CV2021★ 2 cited

Training dataset generation for bridge game registration

Piotr Wzorek, Tomasz Kryjak

This paper presents a method for automatic generation of a training dataset for a deep convolutional neural network used for playing card detection. The solution allows to skip the…