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Tomasz Kryjak
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2020 – today
- 2024
- [c61]Kamil Jeziorek
, Piotr Wzorek
Optimising Graph Representation for Hardware Implementation of Graph Convolutional Networks for Event-Based Vision. DASIP 2024: 110-122 - [c60]Hubert Szolc, Karol Desnos, Tomasz Kryjak:
Tangled Program Graphs as an alternative to DRL-based control algorithms for UAVs. SPA 2024: 36-41 - [i30]Kamil Jeziorek, Piotr Wzorek, Krzysztof Blachut, Andréa Pinna, Tomasz Kryjak:
Optimising Graph Representation for Hardware Implementation of Graph Convolutional Networks for Event-based Vision. CoRR abs/2401.04988 (2024) - [i29]Kamil Jeziorek, Piotr Wzorek, Krzysztof Blachut, Andréa Pinna, Tomasz Kryjak:
Embedded Graph Convolutional Networks for Real-Time Event Data Processing on SoC FPGAs. CoRR abs/2406.07318 (2024) - [i28]Dominika Przewlocka-Rus, Tomasz Kryjak, Marek Gorgon:
PowerYOLO: Mixed Precision Model for Hardware Efficient Object Detection with Event Data. CoRR abs/2407.08272 (2024) - [i27]Tomasz Kryjak:
Event-based vision on FPGAs - a survey. CoRR abs/2407.08356 (2024) - 2023
- [c59]Maciej Baczmanski, Mateusz Wasala
Implementation of a Perception System for Autonomous Vehicles Using a Detection-Segmentation Network in SoC FPGA. ARC 2023: 200-211 - [c58]Marcin Kowalczyk
Interpolation-Based Event Visual Data Filtering Algorithms. CVPR Workshops 2023: 4056-4064 - [c57]Mariusz Grabowski
Real-Time FPGA Implementation of the Semi-global Matching Stereo Vision Algorithm for a 4K/UHD Video Stream. DASIP 2023: 70-81 - [c56]Dominika Przewlocka-Rus
Power-of- Two Quantized YOLO Network for Pedestrian Detection with Dynamic Vision Sensor. DSD 2023: 39-45 - [c55]Maciej Baczmanski, Robert Synoczek, Mateusz Wasala
Detection-segmentation convolutional neural network for autonomous vehicle perception. MMAR 2023: 117-122 - [c54]Konrad Lis
Comparative study of subset selection methods for rapid prototyping of 3D object detection algorithms. MMAR 2023: 344-349 - [c53]Krzysztof Blachut
High-definition event frame generation using SoC FPGA devices. SPA 2023: 106-111 - [c52]Kamil Jeziorek, Andréa Pinna, Tomasz Kryjak
Memory-Efficient Graph Convolutional Networks for Object Classification and Detection with Event Cameras. SPA 2023: 160-165 - [i26]Mariusz Grabowski, Tomasz Kryjak:
Real-time FPGA implementation of the Semi-Global Matching stereo vision algorithm for a 4K/UHD video stream. CoRR abs/2301.04847 (2023) - [i25]Piotr Wzorek, Tomasz Kryjak:
Pedestrian detection with high-resolution event camera. CoRR abs/2305.18008 (2023) - [i24]Maciej Baczmanski, Robert Synoczek, Mateusz Wasala, Tomasz Kryjak:
Detection-segmentation convolutional neural network for autonomous vehicle perception. CoRR abs/2306.17485 (2023) - [i23]Konrad Lis, Tomasz Kryjak:
Comparative study of subset selection methods for rapid prototyping of 3D object detection algorithms. CoRR abs/2306.17551 (2023) - [i22]Maciej Baczmanski, Mateusz Wasala, Tomasz Kryjak:
Implementation of a perception system for autonomous vehicles using a detection-segmentation network in SoC FPGA. CoRR abs/2307.08682 (2023) - [i21]Kamil Jeziorek, Andréa Pinna, Tomasz Kryjak:
Memory-Efficient Graph Convolutional Networks for Object Classification and Detection with Event Cameras. CoRR abs/2307.14124 (2023) - [i20]Krzysztof Blachut, Tomasz Kryjak:
High-definition event frame generation using SoC FPGA devices. CoRR abs/2307.14177 (2023) - [i19]Pawel Miera, Hubert Szolc, Tomasz Kryjak:
LiDAR-based drone navigation with reinforcement learning. CoRR abs/2307.14313 (2023) - 2022
- [j14]Dominika Przewlocka-Rus
The bioinspired traffic sign classifier. Bio Algorithms Med Syst. 18(1): 29-38 (2022) - [j13]Krzysztof Blachut
Real-Time Efficient FPGA Implementation of the Multi-Scale Lucas-Kanade and Horn-Schunck Optical Flow Algorithms for a 4K Video Stream. Sensors 22(13): 5017 (2022) - [j12]Tomasz Kryjak, Andréa Pinna:
Guest Editorial: Special Issue on Design and Architectures for Signal and Image Processing 2021. J. Signal Process. Syst. 94(7): 621-622 (2022) - [j11]Krzysztof Blachut
Automotive Perception System Evaluation with Reference Data from a UAV's Camera Using ArUco Markers and DCNN. J. Signal Process. Syst. 94(7): 675-692 (2022) - [c51]Michal Danilowicz
Real-Time Embedded Object Tracking with Discriminative Correlation Filters Using Convolutional Features. ARC 2022: 166-180 - [c50]Dominika Przewlocka-Rus
Towards Real-Time and Energy Efficient Siamese Tracking - A Hardware-Software Approach. DASIP 2022: 162-173 - [c49]Marcin Kowalczyk
Hardware architecture for high throughput event visual data filtering with matrix of IIR filters algorithm. DSD 2022: 284-291 - [c48]Sylwia Kuros
Traffic Sign Classification Using Deep and Quantum Neural Networks. ICCVG 2022: 43-55 - [c47]Konrad Lis
PointPillars Backbone Type Selection for Fast and Accurate LiDAR Object Detection. ICCVG 2022: 99-119 - [c46]Dominika Przewlocka-Rus
Energy Efficient Hardware Acceleration of Neural Networks with Power-of-Two Quantisation. ICCVG 2022: 225-236 - [c45]Mateusz Wasala
Real-time HOG+SVM based object detection using SoC FPGA for a UHD video stream. MECO 2022: 1-6 - [c44]Piotr Wzorek
Traffic Sign Detection With Event Cameras and DCNN. SPA 2022: 86-91 - [c43]Hubert Szolc
Hardware-in-the-loop simulation of a UAV autonomous landing algorithm implemented in SoC FPGA. SPA 2022: 135-140 - [i18]Mateusz Wasala, Tomasz Kryjak:
Real-time HOG+SVM based object detection using SoC FPGA for a UHD video stream. CoRR abs/2204.10619 (2022) - [i17]Dominika Przewlocka-Rus, Tomasz Kryjak:
Towards real-time and energy efficient Siamese tracking - a hardware-software approach. CoRR abs/2205.10653 (2022) - [i16]Marcin Kowalczyk, Tomasz Kryjak:
Hardware architecture for high throughput event visual data filtering with matrix of IIR filters algorithm. CoRR abs/2207.00860 (2022) - [i15]Hubert Szolc, Tomasz Kryjak:
Hardware-in-the-loop simulation of a UAV autonomous landing algorithm implemented in SoC FPGA. CoRR abs/2207.12198 (2022) - [i14]Piotr Wzorek, Tomasz Kryjak:
Traffic Sign Detection With Event Cameras and DCNN. CoRR abs/2207.13345 (2022) - [i13]Sylwia Kuros, Tomasz Kryjak:
Traffic Sign Classification Using Deep and Quantum Neural Networks. CoRR abs/2209.15251 (2022) - [i12]Konrad Lis, Tomasz Kryjak:
PointPillars Backbone Type Selection For Fast and Accurate LiDAR Object Detection. CoRR abs/2209.15252 (2022) - [i11]Dominika Przewlocka-Rus, Tomasz Kryjak:
Energy Efficient Hardware Acceleration of Neural Networks with Power-of-Two Quantisation. CoRR abs/2209.15257 (2022) - [i10]Kamil Bialik, Marcin Kowalczyk, Krzysztof Blachut, Tomasz Kryjak:
Fast-moving object counting with an event camera. CoRR abs/2212.08384 (2022) - [i9]Kamil Jeziorek, Tomasz Kryjak:
Traffic sign detection and recognition using event camera image reconstruction. CoRR abs/2212.08387 (2022) - 2021
- [j10]Marcin Kowalczyk
Real-Time FPGA Implementation of Parallel Connected Component Labelling for a 4K Video Stream. J. Signal Process. Syst. 93(5): 481-498 (2021) - [c42]Dominika Przewlocka-Rus
Exploration of Hardware Acceleration Methods for an XNOR Traffic Signs Classifier. CORES/IP&C/ACS 2021: 34-45 - [c41]Krzysztof Blachut
Automotive perception system evaluation with reference data obtained by a UAV. DASIP 2021: 10-18 - [c40]Joanna Stanisz
Hardware-software implementation of the PointPillars network for 3D object detection in point clouds. DASIP 2021: 44-51 - [c39]Marcin Kowalczyk
A Connected Component Labelling algorithm for a multi-pixel per clock cycle video stream. DSD 2021: 43-50 - [c38]Joanna Stanisz
Hardware-software implementation of a DNN for 3D object detection using FINN - a demo. FPL 2021: 398 - [c37]Marcin Kowalczyk
A comparison of real-time 4K/UltraHD connected component labelling architectures. FPL 2021: 401 - [c36]Dominika Przewlocka-Rus
Quantised Siamese Tracker for 4K/UltraHD Video Stream - a demo. FPL 2021: 405 - [c35]Artur Cyba, Hubert Szolc
A simple vision-based navigation and control strategy for autonomous drone racing. MMAR 2021: 185-190 - [e1]Tomasz Kryjak, Andrea Pinna:
DASIP '21: Workshop on Design and Architectures for Signal and Image Processing (14th edition) - in conjunction with HiPEAC 2021, Budapest, Hungary, January 18-20, 2021. ACM 2021, ISBN 978-1-4503-8901-3 [contents] - [i8]Dominika Przewlocka-Rus, Marcin Kowalczyk, Tomasz Kryjak:
Exploration of Hardware Acceleration Methods for an XNOR Traffic Signs Classifier. CoRR abs/2104.02303 (2021) - [i7]Artur Cyba, Hubert Szolc, Tomasz Kryjak:
A simple vision-based navigation and control strategy for autonomous drone racing. CoRR abs/2104.09815 (2021) - [i6]Marcin Kowalczyk, Tomasz Kryjak:
A Connected Component Labelling algorithm for multi-pixel per clock cycle video stream. CoRR abs/2105.09658 (2021) - [i5]Piotr Wzorek
Training dataset generation for bridge game registration. CoRR abs/2109.11861 (2021) - 2020
- [c34]Krzysztof Blachut
A Vision Based Hardware-Software Real-Time Control System for the Autonomous Landing of an UAV. ICCVG 2020: 13-24 - [c33]Dominika Przewlocka
Optimisation of a Siamese Neural Network for Real-Time Energy Efficient Object Tracking. ICCVG 2020: 151-163 - [c32]Piotr Janus, Tomasz Kryjak
Foreground Object Segmentation in RGB-D Data Implemented on GPU. KKA 2020: 809-820 - [c31]Joanna Stanisz, Konrad Lis, Tomasz Kryjak, Marek Gorgon:
Optimisation of the PointPillars network for 3D object detection in point clouds. SPA 2020: 122-127 - [i4]Piotr Janus, Tomasz Kryjak, Marek Gorgon:
Foreground object segmentation in RGB-D data implemented on GPU. CoRR abs/2002.00250 (2020) - [i3]Krzysztof Blachut, Hubert Szolc, Mateusz Wasala, Tomasz Kryjak, Marek Gorgon:
Vision based hardware-software real-time control system for autonomous landing of an UAV. CoRR abs/2004.11612 (2020) - [i2]Dominika Przewlocka, Mateusz Wasala, Hubert Szolc, Krzysztof Blachut, Tomasz Kryjak:
Optimisation of a Siamese Neural Network for Real-Time Energy Efficient Object Tracking. CoRR abs/2007.00491 (2020) - [i1]Joanna Stanisz, Konrad Lis, Tomasz Kryjak, Marek Gorgon:
Optimisation of the PointPillars network for 3D object detection in point clouds. CoRR abs/2007.00493 (2020)
2010 – 2019
- 2019
- [c30]Piotr Ciarach, Marcin Kowalczyk
Real-Time FPGA Implementation of Connected Component Labelling for a 4K Video Stream. ARC 2019: 165-180 - [c29]Marcin Kowalczyk
Real-Time Implementation of Adaptive Correlation Filter Tracking for 4K Video Stream in Zynq UltraScale+ MPSoC. DASIP 2019: 53-58 - 2018
- [j9]Tomasz Kryjak
Real-time hardware-software embedded vision system for ITS smart camera implemented in Zynq SoC. J. Real Time Image Process. 15(1): 123-159 (2018) - [c28]Kamil Piszczek, Piotr Janus, Tomasz Kryjak
The Use of HACP+SBT Lossless Compression in Optimizing Memory Bandwidth Requirement for Hardware Implementation of Background Modelling Algorithms. ARC 2018: 379-391 - [c27]Marcin Kowalczyk
Real-Time Implementation of Contextual Image Processing Operations for 4K Video Stream in Zynq UltraScale+ MPSoC. DASIP 2018: 37-42 - [c26]Karol Radwan, Tomasz Kryjak
Hardware-Software Implementation of a SFM Module for Navigation an Unmanned Aerial Vehicles-A Demo. DASIP 2018: 60-61 - [c25]Patryk Fraczek, André Mora
Embedded Vision System for Automated Drone Landing Site Detection. ICCVG 2018: 397-409 - [c24]Piotr Janus, Tomasz Kryjak
Hardware implementation of the Gaussian Mixture Model foreground object segmentation algorithm working with ultra-high resolution video stream in real-time. SPA 2018: 140-145 - 2017
- [c23]Marcin Kowalczyk, Tomasz Kryjak
Object tracking with the use of a moving camera implemented in heterogeneous zynq SoC - A demo. DASIP 2017: 1-2 - [c22]Tomasz Kryjak
Hardware-software abandoned object detection vision system in heterogeneous zynq device. DASIP 2017: 1-2 - [c21]Marcin Kowalczyk
Object Tracking With the Use of a Moving Camera Implemented in Heterogeneous Zynq System on Chip. KKA 2017: 354-363 - [c20]Bartosz Meus, Tomasz Kryjak
Embedded vision system for pedestrian detection based on HOG+SVM and use of motion information implemented in Zynq heterogeneous device. SPA 2017: 406-411 - 2016
- [c19]Piotr Augustyniak, Miroslaw Jablonski, Eliasz Kantoch, Tomasz Kryjak, Zbigniew Mikrut, Elzbieta Pociask, Jaromir Przybylo:
Using Scanpath Analysis for Affects Detection in Computer Users. AfCAI 2016 - [c18]Tomasz Kryjak
An Efficient Hardware Architecture for Block Based Image Processing Algorithms. ARC 2016: 54-65 - [c17]Walter Stechele, Tomasz Kryjak, Lionel Lacassagne, Dominique Houzet, Martin Danek:
Special session 1 automotive parallel computing challenges - architectures, applications and tricks. DASIP 2016: 161 - [c16]Mateusz Komorkiewicz, Krzysztof Turek, Pawel Skruch, Tomasz Kryjak
FPGA-based Hardware-in-the-Loop environment using video injection concept for camera-based systems in automotive applications. DASIP 2016: 183-190 - [c15]Bartlomiej Hebda, Tomasz Kryjak
A compact deep convolutional neural network architecture for video based age and gender estimation. FedCSIS 2016: 787-790 - [c14]Piotr Janus, Kamil Piszczek, Tomasz Kryjak
FPGA Implementation of the Flux Tensor Moving Object Detection Method. ICCVG 2016: 486-497 - 2015
- [c13]Mateusz Komorkiewicz, Tomasz Kryjak
FPGA based system for real-time structure from motion computation. DASIP 2015: 1-7 - [c12]Tomasz Kryjak
Shape and colour recognition of dishes for the purpose of customer service process automation in a self-service canteen. FedCSIS 2015: 799-808 - [c11]Tomasz Kryjak
Real-Time Implementation of Background Modelling Algorithms in FPGA Devices. ICIAP Workshops 2015: 519-526 - 2014
- [j8]Tomasz Kryjak
Real-time implementation of foreground object detection from a moving camera using the ViBe algorithm. Comput. Sci. Inf. Syst. 11(4): 1617-1637 (2014) - [j7]Tomasz Kryjak
Real-time background generation and foreground object segmentation for high-definition colour video stream in FPGA device. J. Real Time Image Process. 9(1): 61-77 (2014) - [j6]Mateusz Komorkiewicz, Tomasz Kryjak
Efficient Hardware Implementation of the Horn-Schunck Algorithm for High-Resolution Real-Time Dense Optical Flow Sensor. Sensors 14(2): 2860-2891 (2014) - [c10]Tomasz Kryjak
Hardware-software implementation of vehicle detection and counting using virtual detection lines. DASIP 2014: 1-8 - [c9]Tomasz Kryjak, Jorge Portilla:
Demo night. DASIP 2014: 1 - [c8]Bartlomiej Bulat, Tomasz Kryjak, Marek Gorgon:
Implementation of Advanced Foreground Segmentation Algorithms GMM, ViBE and PBAS in FPGA and GPU - A Comparison. ICCVG 2014: 124-131 - 2013
- [c7]Tomasz Kryjak, Marek Gorgon:
Real-time Implementation of the ViBe Foreground Object Segmentation Algorithm. FedCSIS 2013: 591-596 - [c6]Tomasz Kryjak, Mateusz Komorkiewicz, Marek Gorgon:
Hardware implementation of the PBAS foreground detection method in FPGA. MIXDES 2013: 479-484 - 2012
- [j5]Tomasz Kryjak, Marek Gorgon:
Pipeline Implementation of Peer Group Filtering in FPGA. Comput. Informatics 31(4): 727- (2012) - [c5]Tomasz Kryjak, Mateusz Komorkiewicz, Marek Gorgon:
FPGA implementation of camera tamper detection in real-time. DASIP 2012: 1-8 - [c4]Tomasz Kryjak, Mateusz Komorkiewicz, Marek Gorgon:
FPGA implementation of real-time head-shoulder detection using local binary patterns, SVM and foreground object detection. DASIP 2012: 1-8 - [c3]Tomasz Kryjak, Mateusz Komorkiewicz, Marek Gorgon:
Is FPGA a suitable platform for advanced video surveillance systems? DASIP 2012: 1-2 - 2011
- [j4]Tomasz Kryjak, Marek Gorgon:
Real-Time Implementation of Moving Object Detection in Video Surveillance Systems using FPGA. Comput. Sci. 12: 149-162 (2011) - [j3]Malgorzata Wlodarczyk, Tomasz Kryjak, Piotr Wolski:
Effectiveness analysis of selected attention models. Bio Algorithms Med Syst. 7(1): 49-56 (2011) - [c2]Tomasz Kryjak
Real-time moving object detection for video surveillance system in FPGA. DASIP 2011: 209-216 - 2010
- [j2]Tomasz Kryjak
Parallel implementation of local thresholding in Mitrion-C. Int. J. Appl. Math. Comput. Sci. 20(3): 571-580 (2010) - [j1]Malgorzata Wlodarczyk, Tomasz Kryjak, Piotr Wolski:
Effectiveness analysis of selected attention models. Bio Algorithms Med Syst. 6(12-S): 217-218 (2010)
2000 – 2009
- 2009
- [c1]Tomasz Kryjak
Pipeline implementation of the 128-bit block cipher CLEFIA in FPGA. FPL 2009: 373-378
Coauthor Index
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last updated on 2024-11-11 22:22 CET by the dblp team
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