PhD Tomasz Kryjak | Embedded Vision Systems Group

Phd Tomasz Kryjak
Research and teaching assistant
Head of the Group
kryjak@agh.edu.pl

I am interested in embedded vision systems for autonomous vehicles, drones and advanced automated video surveillance. I implement these in FPGAs and reprogrammable heterogeneous devices. I also work with event cameras, neuromorphic computing and embedded AI systems.

Recent Committees (Selected)

PLDI’26 (PC), ICSE’26 (PC), ECOOP’26 (PC), POPL’26 SCR (PC)
ASE’25 (PC), ISSTA’25 (PC), ICSME’25 (PC), ICSE’25 NIER (PC)
ECOOP’24 (Co-Chair), OOPSLA’24 (PC), ISSTA’24 (PC), ICSE’24 NIER (PC), PROGRAMMING’24 (PC)
ECOOP’23 (Co-Chair), ICSME’23 (PC), ISSTA’23 (PC), OOPSLA’23 (PC), ICSE’23 NIER (PC)
ICSE’22 (PC), ECOOP’22 (PC)
ESOP’21 (PC)
ECOOP’20 (PC), ICFP’20 (ERC), PROGRAMMING’20 (PC)

Reviewer for Journals

IEEE Transactions on Software Engineering (TSE)
ACM Transactions on Software Engineering and Methodology (TOSEM)
Springer International Journal on Very Large Data Bases (VLDB)
Elsevier Journal of Systems and Software (JSS)
Elsevier Science of Computer Programming
IEEE Transactions on Computers
Elsevier Journal of Computer Languages
Elsevier Knowledge-based Engineering
IEEE Internet Computing
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Springer Empirical Software Engineering
Elsevier Information and Software Technology
Elsevier Pervasive and Mobile Computing
LNCS Transactions on Aspect-Oriented Software Development

Organization of Scientific Events

The ACM DEBS’19 conference (with Boris Koldehofe)
Dagstuhl Seminar “Programming Languages for Distributed Systems and Distributed Data Management” (19442), 2019
NII Shonan Meeting on “Programming Languages for Distributed Systems”, 2019
REBLS workshop series at Splash: REBLS’21,’20,’19,’18,’17,’16,’15,’14,REM’13
COP’16 workshop at ECOOP

Publications

2024

SPA
Preludium

Tangled Program Graphs as an alternative to DRL-based control algorithms for UAVs

Hubert Szolc, Karol Desnos, and Tomasz Kryjak

In 2024 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA) , Sep 2024

Awarded Abstract DOI arXiv Bib Code Poster Website

Best Paper Award

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 the real environment with a human-level performance. Despite very good results in terms of selected metrics, this approach has some significant drawbacks: high computational requirements and low explainability. Because of that, a DRL-based agent cannot be used in some control tasks, especially when safety is the key issue. Therefore we propose to use Tangled Program Graphs (TPGs) as an alternative for deep reinforcement learning in control-related tasks. In this approach, input signals are processed by simple programs that are combined in a graph structure. As a result, TPGs are less computationally demanding and their actions can be explained based on the graph structure. In this paper, we present our studies on the use of TPGs as an alternative for DRL in control-related tasks. In particular, we consider the problem of navigating an unmanned aerial vehicle (UAV) through the unknown environment based solely on the onboard LiDAR sensor. The results of our work show promising prospects for the use of TPGs in control related-tasks.
@inproceedings{10715635, author = {Szolc, Hubert and Desnos, Karol and Kryjak, Tomasz}, booktitle = {2024 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)}, title = {Tangled Program Graphs as an alternative to DRL-based control algorithms for UAVs}, year = {2024}, volume = {}, number = {}, pages = {36--41}, keywords = {Measurement;Laser radar;Navigation;Signal processing algorithms;Process control;Computer architecture;Deep reinforcement learning;Autonomous aerial vehicles;Safety;Tangled Program Graphs;TPG;Deep Reinforcement Learning;DRL;control algorithms;unmanned aerial vehicle;UAV}, doi = {10.23919/SPA61993.2024.10715635}, issn = {2326-0319}, month = sep, projects = {Preludium}, acronym = {SPA}, }
Event-based vision on FPGAs – a survey

Tomasz Kryjak

In , Sep 2024

DOI
Optimising graph representation for hardware implementation of graph convolutional networks for event-based vision

Kamil Jeziorek, Piotr Wzorek, Krzysztof Blachut, Andrea Pinna, and Tomasz Kryjak

In , Sep 2024

DOI
PowerYOLO: mixed precision model for hardware efficient object detection with event data

Dominika Przewlocka-Rus, Tomasz Kryjak, and Marek Gorgon

In , Sep 2024

DOI

2023

Comparative study of subset selection methods for rapid prototyping of 3D object detection algorithms

Konrad Lis and Tomasz Kryjak

In , Sep 2023

DOI
Preludium

Detection-segmentation convolutional neural network for autonomous vehicle perception

Maciej Baczmanski, Robert Synoczek, Mateusz Wasala, and Tomasz Kryjak

In , Sep 2023

DOI
Energy efficient hardware acceleration of neural networks with power-of-two quantisation

Dominika Przewlocka-Rus and Tomasz Kryjak

In , Sep 2023

DOI
High-definition event frame generation using SoC FPGA devices

Krzysztof Blachut and Tomasz Kryjak

In , Sep 2023

DOI
Preludium

Implementation of a perception system for autonomous vehicles using a detection-segmentation network in SoC FPGA

Maciej Baczmanski, Mateusz Wasala, and Tomasz Kryjak

In , Sep 2023

DOI
Interpolation-based event visual data filtering algorithms

Marcin Kowalczyk and Tomasz Kryjak

In , Sep 2023

DOI
Memory-efficient graph convolutional networks for object classification and detection with event cameras

Kamil Jeziorek, Andrea Pinna, and Tomasz Kryjak

In , Sep 2023

DOI
Pedestrian detection with high-resolution event camera

Piotr Wzorek and Tomasz Kryjak

Sep 2023

DOI
PointPillars backbone type selection for fast and accurate LiDAR object detection

Konrad Lis and Tomasz Kryjak

In , Sep 2023

DOI
Power-of-two quantized YOLO network for pedestrian detection with dynamic vision sensor

Dominika Przewlocka-Rus and Tomasz Kryjak

In , Sep 2023

DOI
Real-time FPGA implementation of the semi-global matching stereo vision algorithm for a 4K/UHD video stream

Mariusz Grabowski and Tomasz Kryjak

In , Sep 2023

DOI
Sterowanie autonomicznym bezzalogowym statkiem powietrznym z wykorzystaniem uczenia przez wzmacnianie

Pawel Miera, Hubert Szolc, and Tomasz Kryjak

PAR Pomiary Automatyka Robotyka, Sep 2023

DOI
Traffic sign classification using deep and quantum neural networks

Sylwia Kuros and Tomasz Kryjak

In , Sep 2023

DOI
Zliczanie szybkich obiektów z wykorzystaniem kamery zdarzeniowej

Kamil Bialik, Marcin Kowalczyk, Krzysztof Blachut, and Tomasz Kryjak

PAR Pomiary Automatyka Robotyka, Sep 2023

DOI

2022

Accelerated training of object detection DNNs for embedded vision systems

Michal Machura, Piotr Wzorek, Tomasz Kryjak, and Marek Gorgon

In , Sep 2022
An efficient real-time FPGA-based ORB feature extraction for an UHD video stream for embedded visual SLAM

Mateusz Wasala, Hubert Szolc, and Tomasz Kryjak

Electronics, Sep 2022

DOI
Automotive perception system evaluation with reference data from a UAV’s camera using ArUco markers and DCNN

Krzysztof Blachut, Michal Danilowicz, Hubert Szolc, Mateusz Wasala, Tomasz Kryjak, and 1 more author

Journal of Signal Processing Systems for Signal, Image, and Video Technology, Sep 2022

DOI
Embedded object detection with custom LittleNet, FINN and vitis AI DCNN accelerators

Michal Machura, Michal Danilowicz, and Tomasz Kryjak

Journal of Low Power Electronics and Applications, Sep 2022

DOI
Exploration of hardware acceleration methods for an XNOR traffic signs classifier

Dominika Przewlocka-Rus, Marcin Kowalczyk, and Tomasz Kryjak

In , Sep 2022

DOI
Guest Editorial: special issue on Design and Architectures for Signal and Image Processing 2021

Tomasz Kryjak and Andrea Pinna

Journal of Signal Processing Systems for Signal, Image, and Video Technology, Sep 2022

DOI
Hardware architecture for high throughput event visual data filtering with matrix of IIR filters algorithm

Marcin Kowalczyk and Tomasz Kryjak

In , Sep 2022

DOI
Hardware-in-the-loop simulation of a UAV autonomous landing algorithm implemented in SoC FPGA

Hubert Szolc and Tomasz Kryjak

In , Sep 2022

DOI
Najmłodszy oddział IEEE w Polsce - co można zdziałać w 3 lata?

Marek Dlugosz, Jacek Izydorczyk, Adrian Kliks, Mateusz Komorkiewicz, Tomasz Kryjak, and 2 more authors

Elektronika : Konstrukcje, Technologie, Zastosowania, Sep 2022

DOI
Playing cards and bidding calls detection for automatic registration of a duplicate bridge game

Piotr Wzorek and Tomasz Kryjak

In , Sep 2022
Real-time CLAHE algorithm implementation in SoC FPGA device for 4K UHD video stream

Tomasz Kryjak, Krzysztof Blachut, Hubert Szolc, and Mateusz Wasala

Electronics, Sep 2022

DOI
Real-time HOG+SVM based object detection using SoC FPGA for a UHD video stream

Mateusz Wasala and Tomasz Kryjak

In , Sep 2022

DOI
Real-time efficient FPGA implementation of the multi-scale Lucas-Kanade and Horn-Schunck optical flow algorithms for a 4K video stream

Krzysztof Blachut and Tomasz Kryjak

Sensors, Sep 2022

DOI
Real-time embedded object tracking with discriminative correlation filters using convolutional features

Michal Danilowicz and Tomasz Kryjak

In , Sep 2022

DOI
The bioinspired traffic sign classifier

Dominika Przewlocka-Rus and Tomasz Kryjak

Bio-Algorithms and Med-Systems, Sep 2022

DOI
Towards real-time and energy efficient Siamese tracking – a hardware-software approach

Dominika Przewlocka-Rus and Tomasz Kryjak

In , Sep 2022

DOI
Traffic sign detection and recognition using event camera image reconstruction

Kamil Jeziorek and Tomasz Kryjak

Zeszyty Studenckiego Towarzystwa Naukowego, Sep 2022
Traffic sign detection with event cameras and DCNN

Piotr Wzorek and Tomasz Kryjak

In , Sep 2022

DOI
Wbudowany system percepcji i sterowania dla modelu pojazdu autonomicznego

Maciej Baczmanski, Balbina Molerus, Robert Synoczek, and Tomasz Kryjak

Sep 2022
Wbudowany system percepcji i sterowania dla modelu pojazdu autonomicznego

Maciej Baczmanski, Balbina Molerus, Robert Synoczek, and Tomasz Kryjak

In , Sep 2022

2021

A comparison of real-time 4K/UltraHD connected component labelling architectures

Marcin Kowalczyk and Tomasz Kryjak

In , Sep 2021

DOI
A connected component labelling algorithm for a multi-pixel per clock cycle video stream

Marcin Kowalczyk and Tomasz Kryjak

In , Sep 2021

DOI
A simple vision-based navigation and control strategy for autonomous drone racing

Artur Cyba, Hubert Szolc, and Tomasz Kryjak

In , Sep 2021

DOI
Automotive perception system evaluation with reference data obtained by a UAV

Krzysztof Blachut, Michal Danilowicz, Hubert Szolc, Mateusz Wasala, Tomasz Kryjak, and 2 more authors

In , Sep 2021

DOI
Hardware-software implementation of a DNN for 3D object detection using FINN - a demo

Joanna Lis, Konrad Lis, Tomasz Kryjak, and Marek Gorgon

In , Sep 2021

DOI
Hardware-software implementation of the PointPillars network for 3D object detection in point clouds

Joanna Lis, Konrad Lis, Tomasz Kryjak, and Marek Gorgon

In , Sep 2021

DOI
Quantised Siamese tracker for 4K/UltraHD video stream – a demo

Dominika Przewlocka-Rus and Tomasz Kryjak

In , Sep 2021

DOI
Real-time FPGA implementation of parallel connected component labelling for a 4K video stream

Marcin Kowalczyk, Piotr Ciarach, Dominika Przewlocka-Rus, Hubert Szolc, and Tomasz Kryjak

Journal of Signal Processing Systems for Signal, Image, and Video Technology, Sep 2021

DOI
The bioinspired traffic sign classifier

Dominika Przewlocka-Rus and Tomasz Kryjak

Bio-Algorithms and Med-Systems, Sep 2021

DOI
Training dataset generation for automatic registration of a duplicate bridge game

Piotr Wzorek and Tomasz Kryjak

Zeszyty Studenckiego Towarzystwa Naukowego, Sep 2021

2020

A vision based hardwares̄oftware realt̄ime control system for the autonomous landing of an UAV

Krzysztof Blachut, Hubert Szolc, Mateusz Wasala, Tomasz Kryjak, and Marek Gorgon

In , Sep 2020

DOI
Foreground object segmentation in RGB–D data implemented on GPU

Piotr Janus, Tomasz Kryjak, and Marek Gorgon

In , Sep 2020

DOI
Optimisation of a Siamese neural network for realt̄ime energy efficient object tracking

Dominika Przewlocka-Rus, Mateusz Wasala, Hubert Szolc, Krzysztof Blachut, and Tomasz Kryjak

In , Sep 2020

DOI
Optimisation of the PointPillars network for 3D object detection in point clouds

Joanna Lis, Konrad Lis, Tomasz Kryjak, and Marek Gorgon

In , Sep 2020

DOI

2019

Hardware implementation of the SURF feature detector for 4K 4PPC video stream – a demo

Karol Radwan and Tomasz Kryjak

In , Sep 2019
Hardwares̄oftware implementation of car detection system based on LiDAR sensor data - a demo

Joanna Stanisz, Konrad Lis, Tomasz Kryjak, and Marek Gorgon

In , Sep 2019
Realt̄ime FPGA implementation of connected component labelling for a 4K video stream

Piotr Ciarach, Marcin Kowalczyk, Dominika Przewlocka-Rus, and Tomasz Kryjak

In , Sep 2019

DOI
Realt̄ime implementation of adaptive correlation filter tracking for 4K video stream in Zynq UltraScale+ MPSoC

Marcin Kowalczyk, Dominika Przewlocka-Rus, and Tomasz Kryjak

In , Sep 2019

DOI
XNOR CNNs in FPGA: realt̄ime detection and classification of traffic signs in 4K – a demo

Dominika Przewlocka-Rus, Marcin Kowalczyk, and Tomasz Kryjak

In , Sep 2019

2018

Embedded vision system for automated drone landing site detection

Patryk Fraczek, Andre Mora, and Tomasz Kryjak

In , Sep 2018

DOI
Embedded vision system for automated drone landing site detection – a demo

Patryk Fraczek, Andre Mora, and Tomasz Kryjak

In , Sep 2018
Hardware acceleration of face detection using a deep convolutional neural network – a demo

Dominika Przewlocka-Rus and Tomasz Kryjak

In , Sep 2018
Hardware implementation of multis̄cale LucasK̄anade optical flow computation algorithm – a demo

Krzysztof Blachut, Tomasz Kryjak, and Marek Gorgon

In , Sep 2018
Hardware implementation of the Gaussian Mixture Model foreground object segmentation algorithm working with ultrah̄igh resolution video stream in realt̄ime

Piotr Janus and Tomasz Kryjak

In , Sep 2018

DOI
Hardware – software implementation of a SFM module for navigation an unmanned aerial vehicles – a demo

Karol Radwan, Tomasz Kryjak, and Marek Gorgon

In , Sep 2018

DOI
Realt̄ime hardwares̄oftware embedded vision system for ITS smart camera implemented in Zynq SoC

Tomasz Kryjak, Mateusz Komorkiewicz, and Marek Gorgon

Journal of Real-Time Image Processing, Sep 2018

DOI
Realt̄ime implementation of contextual image processing operations for 4K video stream in Zynq UltraScale+ MPSoC

Marcin Kowalczyk, Dominika Przewlocka-Rus, and Tomasz Kryjak

In , Sep 2018

DOI
Realt̄ime implementation of contextual image processing operations for 4K video stream in Zynq UltraScale+ MPSoC – a demo

Marcin Kowalczyk, Dominika Przewlocka-Rus, and Tomasz Kryjak

In , Sep 2018
The use of HACP+SBT lossless compression in optimizing memory bandwidth requirement for hardware implementation of background modelling algorithms

Kamil Piszczek, Piotr Janus, and Tomasz Kryjak

In , Sep 2018

DOI

2017

Demo: embedded vision system for pedestrian detection based on HoG+SVM and use of motion information implemented in Zynq heterogeneous device

Bartosz Meus, Tomasz Kryjak, and Marek Gorgon

In , Sep 2017
Embedded vision system for pedestrian detection based on HOG+SVM and use of motion information implemented in Zynq heterogeneous device

Bartosz Meus, Tomasz Kryjak, and Marek Gorgon

In , Sep 2017

DOI
Hardwares̄oftware abandoned object detection vision system in heterogeneous Zynq device

Tomasz Kryjak, Artur Skirzynski, and Marek Gorgon

In , Sep 2017

DOI
Object tracking using a moving camera based on object detection and connected component labelling implemented in Zynq SoC

Marcin Kowalczyk, Piotr Ciarach, and Tomasz Kryjak

Zeszyty Studenckiego Towarzystwa Naukowego, Sep 2017
Object tracking with the use of a moving camera implemented in heterogeneous Zynq SoC – a demo

Marcin Kowalczyk, Tomasz Kryjak, and Marek Gorgon

In , Sep 2017
Object tracking with the use of a moving camera implemented in heterogeneous Zynq System on Chip

Marcin Kowalczyk and Tomasz Kryjak

In , Sep 2017

DOI

2016

A compact deep convolutional neural network architecture for video based age and gender estimation

Bartlomiej Hebda and Tomasz Kryjak

In , Sep 2016

DOI
An efficient hardware architecture for block based image processing algorithms

Tomasz Kryjak, Marek Gorgon, and Mateusz Komorkiewicz

In , Sep 2016

DOI
An embedded visionb̄ased tracking system for autonomous robot navigation

Krzysztof Mazur and Tomasz Kryjak

Measurement Automation and Monitoring, Sep 2016
Demo: FPGA implementation of the flux tensor moving object detection method

Piotr Janus, Kamil Piszczek, Tomasz Kryjak, and Marek Gorgon

In , Sep 2016
Demo: an embedded vision system supporting the home care for convalescent or elderly people

Piotr Konopka, Tomasz Jonak, Tomasz Kryjak, and Marek Gorgon

In , Sep 2016
Demo: autonomous vehicle model with visionb̄ased tracking system

Krzysztof Mazur, Tomasz Kryjak, and Marek Gorgon

In , Sep 2016
FPGA implementation of multis̄cale face detection using HOG features and SVM classifier

Michal Drożdż and Tomasz Kryjak

Image Processing & Communications, Sep 2016
FPGA implementation of multis̄cale pedestrian detection in thermal images

Tomasz Kanka, Tomasz Kryjak, and Marek Gorgon

Image Processing & Communications, Sep 2016
FPGA implementation of the flux tensor moving object detection method

Piotr Janus, Kamil Piszczek, and Tomasz Kryjak

In , Sep 2016

DOI
FPGAb̄ased hardwareīnt̄hel̄oop environment using video injection concept for camerab̄ased systems in automotive applications

Mateusz Komorkiewicz, Pawel Skruch, Tomasz Kryjak, Krzysztof Turek, and Marek Gorgon

In , Sep 2016
Using scanpath analysis for affects detection in computer users

Piotr Augustyniak, Miroslaw Jablonski, Eliasz Kantoch, Tomasz Kryjak, Zbigniew Mikrut, and 2 more authors

In , Sep 2016

2015

Age, race and gender estimation based on facial images

Bartlomiej Hebda and Tomasz Kryjak

Zeszyty Studenckiego Towarzystwa Naukowego, Sep 2015
FPGA based system for realt̄ime structure from motion computation

Mateusz Komorkiewicz, Tomasz Kryjak, Katarzyna Chuchacz-Kowalczyk, Pawel Skruch, and Marek Gorgon

In , Sep 2015
Realt̄ime implementation of background modelling algorithms in FPGA devices

Tomasz Kryjak and Marek Gorgon

In , Sep 2015

DOI
Segmentation of dishes for customer service automation in a selfs̄ervice canteen

Tomasz Kryjak, Damian Król, and Marek Gorgon

Image Processing & Communications, Sep 2015

DOI
Segmentation of dishes for the purposes of customer service process automation in a selfs̄ervice canteen

Tomasz Kryjak, Damian Król, and Marek Gorgon

In , Sep 2015
Shape and colour recognition of dishes for the purpose of customer service process automation in a selfs̄ervice canteen

Tomasz Kryjak and Damian Król

In , Sep 2015

DOI

2014

Efficient hardware implementation of the HornS̄chunck algorithm for highr̄esolution realt̄ime dense optical flow sensor

Mateusz Komorkiewicz, Tomasz Kryjak, and Marek Gorgon

Sensors, Sep 2014

DOI
Foreground object segmentation in dynamic background scenarios

Tomasz Kryjak

Image Processing & Communications, Sep 2014

DOI
Hardwares̄oftware implemantation of vehicle detection and counting using virtual detection lines

Tomasz Kryjak, Mateusz Komorkiewicz, and Marek Gorgon

In , Sep 2014

DOI
Implementacja zaawansowanych algorytmów przetwarzania i analizy obrazów oraz szyfrowania w układach reprogramowalnych

Tomasz Kryjak

Sep 2014
Implementacja zaawansowanych algorytmów przetwarzania i analizy obrazów oraz szyfrowania w układach reprogramowalnych [Dokument elektroniczny]

Tomasz Kryjak

Sep 2014
Implementation of advanced foreground segmentation algorithms GMM, ViBE and PBAS in FPGA and GPU – a comparison

Bartlomiej Bulat, Tomasz Kryjak, and Marek Gorgon

In , Sep 2014

DOI
Realt̄ime background generation and foreground object segmentation for highd̄efinition colour video stream in FPGA device

Tomasz Kryjak, Mateusz Komorkiewicz, and Marek Gorgon

Journal of Real-Time Image Processing, Sep 2014

DOI
Realt̄ime foreground object detection combining the PBAS background modelling algorithm and feedback from scene analysis module

Tomasz Kryjak, Mateusz Komorkiewicz, and Marek Gorgon

International Journal of Electronics and Telecommunications, Sep 2014

DOI