3 citations · 5 across the 14 of their papers we have counts for
15 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…
FPGA-Based Hardware Architecture for Contrast Maximization in Event-Based Vision
Michal Filipkowski, Marcin Kowalczyk, Tomasz Kryjak
This paper presents a hardware architecture that implements the Contrast Maximization (CM) algorithm in Field-Programmable Gate Array (FPGA) resources for event-based vision system…
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…
SIRA: Scaled-Integer Range Analysis for Optimizing FPGA Dataflow Neural Network Accelerators
Yaman Umuroglu, Christoph Berganski, Felix Jentzsch +8
While neural network quantization effectively reduces the cost of matrix multiplications, aggressive quantization can expose non-matrix-multiply operations as significant performan…
Hardware-Aware Feature Extraction Quantisation for Real-Time Visual Odometry on FPGA Platforms
Mateusz Wasala, Mateusz Smolarczyk, Michal Danilowicz +1
Accurate position estimation is essential for modern navigation systems deployed in autonomous platforms, including ground vehicles, marine vessels, and aerial drones. In this cont…
High Throughput Event Filtering: The Interpolation-based DIF Algorithm Hardware Architecture
Marcin Kowalczyk, Tomasz Kryjak
In recent years, there has been rapid development in the field of event vision. It manifests itself both on the technical side, as better and better event sensors are available, an…
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…
Self-Supervised Event Representations: Towards Accurate, Real-Time Perception on SoC FPGAs
Kamil Jeziorek, Tomasz Kryjak
Event cameras offer significant advantages over traditional frame-based sensors. These include microsecond temporal resolution, robustness under varying lighting conditions and low…
Vision-based automatic fruit counting with UAV
Hubert Szolc, Mateusz Wasala, Remigiusz Mietla +2
The use of unmanned aerial vehicles (UAVs) for smart agriculture is becoming increasingly popular. This is evidenced by recent scientific works, as well as the various competitions…
Real-Time Multi-Object Tracking using YOLOv8 and SORT on a SoC FPGA
Michal Danilowicz, Tomasz Kryjak
Multi-object tracking (MOT) is one of the most important problems in computer vision and a key component of any vision-based perception system used in advanced autonomous mobile ro…
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…
Utilisation of Vision Systems and Digital Twin for Maintaining Cleanliness in Public Spaces
Mateusz Wasala, Krzysztof Blachut, Hubert Szolc +3
Nowadays, the increasing demand for maintaining high cleanliness standards in public spaces results in the search for innovative solutions. The deployment of CCTV systems equipped…
Tangled Program Graphs as an alternative to DRL-based control algorithms for UAVs
Hubert Szolc, Karol Desnos, Tomasz Kryjak
Deep reinforcement learning (DRL) is currently the most popular AI-based approach to autonomous vehicle control. An agent, trained for this purpose in simulation, can interact with…