11 citations · 29 across the 10 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…