Hubert Szolc

2026

1. Automation

   Vision-based automatic fruit counting with UAV

   Hubert Szolc, Mateusz Wasala, Remigiusz Mietla, Kacper Iwicki, and Tomasz Kryjak

   In Automation 2025: recent advances in automation, robotics and measurement techniques, Sep 2026

   Abstract DOI arXiv Bib

   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 organised on this topic. Therefore, in this work we present a system for automatic fruit counting using UAVs. To detect them, our solution uses a vision algorithm that processes streams from an RGB camera and a depth sensor using classical image operations. Our system also allows the planning and execution of flight trajectories, taking into account the minimisation of flight time and distance covered. We tested the proposed solution in simulation and obtained an average score of 87.27/100 points from a total of 500 missions. We also submitted it to the UAV Competition organised as part of the ICUAS 2024 conference, where we achieved an average score of 84.83/100 points, placing 6th in a field of 23 teams and advancing to the finals.

   @inproceedings{badap-agh:165951,
     title = {Vision-based automatic fruit counting with UAV},
     author = {Szolc, Hubert and Wasala, Mateusz and Mietla, Remigiusz and Iwicki, Kacper and Kryjak, Tomasz},
     year = {2026},
     series = {Automation~2025: recent advances in automation, robotics and measurement techniques},
     pages = {243–252},
     doi = {10.1007/978-3-032-08359-3_23},
     collection = {Automation~2025: recent advances in automation, robotics and measurement techniques},
   }

2025

1. SPA

   Embedded perception and control system for an autonomous surface vehicle using visual-LiDAR fusion and SLAM

   Olivier Lichota, Mateusz Wasala, Hubert Szolc, and Tomasz Kryjak

   In SPA 2025 : Signal Processing - algorithms, architectures, arrangements, and applications : Poznan, 17th–19th September 2025 : conference proceedings, Sep 2025

   Abstract DOI Bib

   The paper presents the design and implementation of a modular perception and control system for an autonomous surface vehicle (ASV), developed on a System-on-Module (SoM) embedded platform. The system was created with the goal of participating in the international RoboBoat competition. The high-level architecture integrates data from a stereo camera, LiDAR sensor, and a GNSS unit with an Inertial Measurement Unit (IMU), enabling object detection, simultaneous localization and mapping (SLAM), and autonomous navigation. We evaluated the use of a quantized convolutional neural network (YOLOv11) for object classification, obstacle detection based on LiDAR data, and control module operation using NAV2 within the ROS 2 environment under limited computational resources. Accelerating visual detection algorithms with CUDA and TensorRT libraries on the onboard NVIDIA Jetson Orin Nano platform enabled effective real-time and low-energy classification. Tests carried out in simulation demonstrated the correct operation of the perception and control system. The average runtime of the system using the quantised YOLO model with GPU was 26.01 ms. This equates to an approximate speed increase of 6.7 times compared to inference performed on an ARM processor, and an approximate speed increase of 5.5 times compared to a standard CPU.

   @inproceedings{badap-agh:163124,
     title = {Embedded perception and control system for an autonomous surface vehicle using visual-LiDAR fusion and SLAM},
     author = {Lichota, Olivier and Wasala, Mateusz and Szolc, Hubert and Kryjak, Tomasz},
     year = {2025},
     series = {SPA~2025 [Dokument elektroniczny] : Signal Processing - algorithms, architectures, arrangements, and applications : Poznan, 17th–19th September~2025 : conference proceedings},
     pages = {153–158},
     doi = {10.23919/SPA65537.2025.11215136},
     collection = {SPA~2025 [Dokument elektroniczny] : Signal Processing - algorithms, architectures, arrangements, and applications : Poznan, 17th–19th September~2025 : conference proceedings},
   }

2024

1. SPA

   

   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

   Abstract Collaboration DOI arXiv Bib

   • VAADER team, Institute of Electronics and Digital Technologies (IETR)
     National Institute of Applied Sciences (INSA) of Rennes, France

   All our collaborations

   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,
     acronym = {SPA}
   }

2023

1. PAR

   Sterowanie autonomicznym bezzalogowym statkiem powietrznym z wykorzystaniem uczenia przez wzmacnianie

   Pawel Miera, Hubert Szolc, and Tomasz Kryjak

   PAR Pomiary Automatyka Robotyka, Sep 2023

   Abstract DOI arXiv Bib

   Reinforcement learning is of increasing importance in the field of robot control and simulation plays a key role in this process. In the unmanned aerial vehicles (UAVs, drones), there is also an increase in the number of published scientific papers involving this approach. In this work, an autonomous drone control system was prepared to fly forward (according to its coordinates system) and pass the trees encountered in the forest based on the data from a rotating LiDAR sensor. The Proximal Policy Optimization (PPO) algorithm, an example of reinforcement learning (RL), was used to prepare it. A custom simulator in the Python language was developed for this purpose. The Gazebo environment, integrated with the Robot Operating System (ROS), was also used to test the resulting control algorithm. Finally, the prepared solution was implemented in the Nvidia Jetson Nano eGPU and verified in the real tests scenarios. During them, the drone successfully completed the set task and was able to repeatable avoid trees and fly through the forest.

   @article{badap-agh:151231,
     title = {Sterowanie autonomicznym bezzalogowym statkiem powietrznym z wykorzystaniem uczenia przez wzmacnianie},
     author = {Miera, Pawel and Szolc, Hubert and Kryjak, Tomasz},
     year = {2023},
     journal = {PAR Pomiary Automatyka Robotyka},
     series = {PAR Pomiary Automatyka Robotyka},
     volume = {27},
     pages = {85},
     doi = {10.14313/PAR_250/85},
     issn = {1427-9126},
     collection = {PAR Pomiary Automatyka Robotyka},
   }

2022

1. Electronics

   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

   Abstract DOI Bib

   The detection and description of feature points are important components of many computer vision systems. For example, in the field of autonomous unmanned aerial vehicles (UAV), these methods form the basis of so-called Visual Odometry (VO) and Simultaneous Localisation and Mapping (SLAM) algorithms. In this paper, we present a hardware feature points detection system able to process a 4K video stream in real-time. We use the ORB algorithm—Oriented FAST (Features from Accelerated Segment Test) and Rotated BRIEF (Binary Robust Independent Elementary Features)—to detect and describe feature points in the images. We make numerous modifications to the original ORB algorithm (among others, we use the RS-BRIEF instead of classic R-BRIEF) to adapt it to the high video resolution, make it computationally efficient, reduce the resource utilisation and achieve lower power consumption. Our hardware implementation supports a 4 ppc (pixels per clock) format (with simple adaptation to 2 ppc, 8 ppc, and more) and real-time processing of a 4K video stream (UHD—Ultra High Definition, 3840×2160 pixels) @ 60 frames per second (150 MHz clock). We verify our system using simulations in the Vivado IDE and implement it in hardware on the ZCU 104 evaluation board with the AMD Xilinx Zynq UltraScale+ MPSoC device. The proposed design consumes only 5 watts.

   @article{badap-agh:141501,
     title = {An efficient real-time FPGA-based ORB feature extraction for an UHD video stream for embedded visual SLAM},
     author = {Wasala, Mateusz and Szolc, Hubert and Kryjak, Tomasz},
     year = {2022},
     journal = {Electronics},
     series = {Electronics},
     volume = {11},
     number = {14},
     pages = {2259},
     doi = {10.3390/electronics11142259},
     issn = {2079-9292},
     collection = {Electronics},
   }

2. JSPS

   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

   Abstract DOI Bib

   Testing and evaluation of an automotive perception system is a complicated task which requires special equipment and infrastructure. To compute key performance indicators and compare the results with real-world situation, some additional sensors and manual data labelling are often required. In this article, we propose a different approach, which is based on a UAV equipped with a 4K camera flying above a test track. Two computer vision methods are used to precisely determine the positions of the objects around the car – one based on ArUco markers and the other on a DCNN (we provide the algorithms used on GitHub). The detections are then correlated with the perception system readings. For the static and dynamic experiments, the differences between various systems are mostly below 0.5 m. The results of the experiments performed indicate that this approach could be an interesting alternative to existing evaluation solutions.

   @article{badap-agh:141200,
     title = {Automotive perception system evaluation with reference data from a UAV's camera using ArUco markers and DCNN},
     author = {Blachut, Krzysztof and Danilowicz, Michal and Szolc, Hubert and Wasala, Mateusz and Kryjak, Tomasz and Komorkiewicz, Mateusz},
     year = {2022},
     journal = {Journal of Signal Processing Systems for Signal, Image, and Video Technology},
     series = {Journal of Signal Processing Systems for Signal, Image, and Video Technology},
     volume = {94},
     number = {7},
     pages = {675},
     doi = {10.1007/s11265-021-01734-3},
     issn = {1939-8018},
     collection = {Journal of Signal Processing Systems for Signal, Image, and Video Technology},
   }

3. SPA

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

   Hubert Szolc and Tomasz Kryjak

   In SPA 2022 : Signal Processing Algorithms, Architectures, Arrangements, and Applications : 25th IEEE SPA conference : Poznan, 21st - 22nd September 2022 : conference proceedings, Sep 2022

   Abstract DOI arXiv Bib

   This paper presents a system for hardware-in-the-loop (HiL) simulation of unmanned aerial vehicle (UAV) control algorithms implemented on a heterogeneous SoC FPGA computing platforms. The AirSim simulator running on a PC and an Arty Z7 development board with a Zynq SoC chip from AMD Xilinx were used. Communication was carried out via a serial USB link. An application for autonomous landing on a specially marked landing strip was selected as a case study. A landing site detection algorithm was implemented on the Zynq SoC platform. This allowed processing a 1280 × 720 @ 60 fps video stream in real time. Performed tests showed that the system works correctly and there are no delays that could negatively affect the stability of the control. The proposed concept is characterised by relative simplicity and low implementation cost. At the same time, it can be applied to test various types of high-level perception and control algorithms for UAV implemented on embedded platforms. We provide the code developed on GitHub, which includes both Python scripts running on the PC and C code running on Arty Z7.

   @inproceedings{badap-agh:143873,
     title = {Hardware-in-the-loop simulation of a UAV autonomous landing algorithm implemented in SoC FPGA},
     author = {Szolc, Hubert and Kryjak, Tomasz},
     year = {2022},
     series = {SPA~2022 [Dokument elektroniczny] : Signal Processing Algorithms, Architectures, Arrangements, and Applications : 25th IEEE SPA conference : Poznan, 21st - 22nd September 2022 : conference proceedings},
     pages = {135–140},
     doi = {10.23919/SPA53010.2022.9927847},
     collection = {SPA~2022 [Dokument elektroniczny] : Signal Processing Algorithms, Architectures, Arrangements, and Applications : 25th IEEE SPA conference : Poznan, 21st - 22nd September 2022 : conference proceedings},
   }

4. Electronics Sonata
   

   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

   Abstract DOI Bib

   One of the problems encountered in the field of computer vision and video data analysis is the extraction of information from low-contrast images. This problem can be addressed in several ways, including the use of histogram equalisation algorithms. In this work, a method designed for this purpose—the Contrast-Limited Adaptive Histogram Equalization (CLAHE) algorithm—is implemented in hardware. An FPGA platform is used for this purpose due to the ability to run parallel computations and very low power consumption. To enable the processing of a 4K resolution (UHD, 3840 × 2160 pixels) video stream at 60 fps (frames per second) by using the CLAHE method, it is necessary to use a vector data format and process multiple pixels simultaneously. The algorithm realised in this work can be a component of a larger vision system, such as in autonomous vehicles or drones, but it can also support the analysis of underwater, thermal, or medical images both by humans and in an automated system.

   @article{badap-agh:141231,
     title = {Real-time CLAHE algorithm implementation in SoC FPGA device for 4K UHD video stream},
     projects = {Sonata},
     author = {Kryjak, Tomasz and Blachut, Krzysztof and Szolc, Hubert and Wasala, Mateusz},
     year = {2022},
     journal = {Electronics},
     series = {Electronics},
     volume = {11},
     number = {14},
     pages = {2248},
     doi = {10.3390/electronics11142248},
     issn = {2079-9292},
     collection = {Electronics},
   }

5. Book chapter Preludium
   

   Systemy wizyjne w zastosowaniach przemyslowych

   Marek Gorgon, Maciej Aleksandrowicz, Krzysztof Blachut, Andrzej Brodzicki, Zbigniew Bublinski, and 20 more authors

   In Nauka – technika – technologia : seria wydawnicza AGH, Sep 2022

   Abstract DOI Bib

   Streszczenie: Systemy wizyjne to dynamicznie rozwijająca się dziedzina nauki i techniki.W niniejszym artykule przedstawiono przegląd zagadnień, nad którymi pracuje zespół Laboratorium Systemów Wizyjnych.Obejmuje on systemy wizyjne dla pojazdów autonomicznych, aplikacje analizy obrazów medycznych, systemy wspomagania szkolenia pracowników, analizę obrazów termowizyjnych, implementacje i akceleracje algorytmów wizyjnych w układach SoC FPGA i GPU, przetwarzanie strumienia wizyjnego w rozdzielczości 4K, a także analizę sygnałów z wykorzystaniem głębokich sieci neuronowych i współpracę przy eksperymencie ALICE w CERN-ie.

   @inbook{badap-agh:141409,
     title = {Systemy wizyjne w zastosowaniach przemyslowych},
     author = {Gorgon, Marek and Aleksandrowicz, Maciej and Blachut, Krzysztof and Brodzicki, Andrzej and Bublinski, Zbigniew and Cyba, Artur and Danilowicz, Michal and Glowacz, Adam and Jablonski, Miroslaw and Jaworek-Korjakowska, Joanna and Kostuch, Aleksander and Kowalczyk, Marcin and Kryjak, Tomasz and Kucharski, Dariusz and Lis, Konrad and Machura, Michal and Mikrut, Zbigniew and Pawlik, Piotr and Piekarski, Michal and Przewlocka-Rus, Dominika and Lis, Joanna and Szolc, Hubert and Wasala, Mateusz and Wojcicka, Anna Malgorzata and Wzorek, Piotr},
     year = {2022},
     projects = {Preludium-Kowalczyk},
     series = {Nauka – technika – technologia : seria wydawnicza AGH},
     volume = {T.~5},
     pages = {17–31},
     doi = {10.7494/978-83-67427-00-5_1},
     collection = {Nauka – technika – technologia : seria wydawnicza AGH},
   }

2021

1. MMAR

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

   Artur Cyba, Hubert Szolc, and Tomasz Kryjak

   In MMAR 2021 : 2021 25th international conference on Methods and Models in Automation & Robotics : August 23–26, 2021, Międzyzdroje, Poland, Sep 2021

   Abstract DOI arXiv Bib

   In this paper, we present a control system that allows a drone to fly autonomously through a series of gates marked with ArUco tags. A simple and low-cost DJI Tello EDU quad-rotor platform was used. Based on the API provided by the manufacturer, we have created a Python application that enables the communication with the drone over WiFi, realises drone positioning based on visual feedback, and generates control. Two control strategies were proposed, compared and critically analysed. In addition, the accuracy of the positioning method used was measured. The application was evaluated on a laptop computer (about 40 fps) and a Nvidia Jetson TX2 embedded GPU platform (about 25 fps). We provide the developed code on GitHub.

   @inproceedings{badap-agh:135661,
     title = {A simple vision-based navigation and control strategy for autonomous drone racing},
     author = {Cyba, Artur and Szolc, Hubert and Kryjak, Tomasz},
     year = {2021},
     series = {MMAR~2021 [Dokument elektroniczny] : 2021~25th~international conference on Methods and Models in Automation \&~Robotics : August 23–26, 2021, Mi\k{e}dzyzdroje, Poland},
     pages = {185–190},
     doi = {10.1109/MMAR49549.2021.9528463},
     collection = {MMAR~2021 [Dokument elektroniczny] : 2021~25th~international conference on Methods and Models in Automation \&~Robotics : August 23–26, 2021, Mi\k{e}dzyzdroje, Poland},
   }

2. DASIP

   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 DASIP 2021 : workshop on Design and Architectures for Signal and Image Processing - 14th edition : January 18–20 2021, Budapest, Hungary : proceedings, Sep 2021

   Abstract DOI Bib

   Testing and evaluation of an automotive perception system is a complicated task which requires special equipment and infrastructure. To compute key performance indicators and compare the results with the real-world situation, some additional sensors and manual data labelling are often required. In this article, we propose a different approach, which is based on a UAV equipped with a 4K camera flying above the test track. Thanks to the synchronisation of the sensors between the tested vehicle and the UAV, it is possible to precisely determine the positions of the objects around the car and correlate them with the perception system readings. The performed experiments indicate that this approach could be an interesting alternative to the existing evaluation solutions.

   @inproceedings{badap-agh:132409,
     title = {Automotive perception system evaluation with reference data obtained by a UAV},
     author = {Blachut, Krzysztof and Danilowicz, Michal and Szolc, Hubert and Wasala, Mateusz and Kryjak, Tomasz and Pankiewicz, Nikodem and Komorkiewicz, Mateusz},
     year = {2021},
     series = {DASIP~2021 [Dokument elektroniczny] : workshop on Design and Architectures for Signal and Image Processing - 14th~edition : January 18–20 2021, Budapest, Hungary : proceedings},
     pages = {10–18},
     doi = {10.1145/3441110.3441151},
     collection = {DASIP~2021 [Dokument elektroniczny] : workshop on Design and Architectures for Signal and Image Processing - 14th~edition : January 18–20 2021, Budapest, Hungary : proceedings},
   }

3. JSPS Sonata
   Preludium
   

   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

   Abstract DOI Bib

   In this paper, a hardware implementation in reconfigurable logic of a single-pass connected component labelling (CCL) and connected component analysis (CCA) module is presented. The main novelty of the design is the support of a video stream in 2 and 4 pixel per clock format (2 and 4 ppc) and real-time processing of 4K/UHD video stream (3840 x 2160 pixels) at 60 frames per second. We discuss several approaches to the issue and present in detail the selected ones. The proposed module was verified in an exemplary application – skin colour areas segmentation – on the ZCU 102 and ZCU 104 evaluation boards equipped with Xilinx Zynq UltraScale+ MPSoC devices.

   @article{badap-agh:134265,
     title = {Real-time FPGA implementation of parallel connected component labelling for a 4K video stream},
     projects = {Sonata, Preludium-Kowalczyk},
     author = {Kowalczyk, Marcin and Ciarach, Piotr and Przewlocka-Rus, Dominika and Szolc, Hubert and Kryjak, Tomasz},
     year = {2021},
     journal = {Journal of Signal Processing Systems for Signal, Image, and Video Technology},
     series = {Journal of Signal Processing Systems for Signal, Image, and Video Technology},
     volume = {93},
     number = {5},
     pages = {481},
     doi = {10.1007/s11265-021-01636-4},
     issn = {1939-8018},
     collection = {Journal of Signal Processing Systems for Signal, Image, and Video Technology},
   }

2020

1. ICCVG

   A vision based hardware-software real-time control system for the autonomous landing of an UAV

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

   In Computer Vision and Graphics : International Conference : ICCVG 2020 : Warsaw, Poland, September 14–16, 2020 : proceedings, Sep 2020

   Abstract DOI arXiv Bib

   In this paper we present a vision based hardware-software control system enabling autonomous landing of a mul-tirotor unmanned aerial vehicle (UAV). It allows the detection of a marked landing pad in real-time for a 1280 x 720 @ 60 fps video stream. In addition, a LiDAR sensor is used to measure the altitude above ground. A heterogeneous Zynq SoC device is used as the computing platform. The solution was tested on a number of sequences and the landing pad was detected with 96% accuracy. This research shows that a reprogrammable heterogeneous computing system is a good solution for UAVs because it enables real-time data stream processing with relatively low energy consumption.

   @inproceedings{badap-agh:130006,
     title = {A vision based hardware-software real-time control system for the autonomous landing of an UAV},
     author = {Blachut, Krzysztof and Szolc, Hubert and Wasala, Mateusz and Kryjak, Tomasz and Gorgon, Marek},
     year = {2020},
     series = {Computer Vision and Graphics : International Conference : ICCVG~2020 : Warsaw, Poland, September 14–16, 2020 : proceedings},
     pages = {13–24},
     doi = {10.1007/978-3-030-59006-2_2},
     collection = {Computer Vision and Graphics : International Conference : ICCVG~2020 : Warsaw, Poland, September 14–16, 2020 : proceedings},
   }

2. ICCVG

   Optimisation of a Siamese neural network for real-time energy efficient object tracking

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

   In Computer Vision and Graphics : International Conference : ICCVG 2020 : Warsaw, Poland, September 14–16, 2020 : proceedings, Sep 2020

   Abstract DOI arXiv Bib

   In this paper the research on optimisation of visual object tracking using a Siamese neural network for embedded vision systems is presented. It was assumed that the solution shall operate in real-time, preferably for a high resolution video stream, with the lowest possible energy consumption. To meet these requirements, techniques such as the reduction of computational precision and pruning were considered. Brevitas, a tool dedicated for optimisation and quantisation of neural networks for FPGA implementation, was used. A number of training scenarios were tested with varying levels of optimisations – from integer uniform quantisation with 16 bits to ternary and binary networks. Next, the influence of these optimisations on the tracking performance was evaluated. It was possible to reduce the size of the convolutional filters up to 10 times in relation to the original network. The obtained results indicate that using quantisation can significantly reduce the memory and computational complexity of the proposed network while still enabling precise tracking, thus allow to use it in embedded vision systems. Moreover, quantisation of weights positively affects the network training by decreasing overfitting.

   @inproceedings{badap-agh:130002,
     title = {Optimisation of a Siamese neural network for real-time energy efficient object tracking},
     author = {Przewlocka-Rus, Dominika and Wasala, Mateusz and Szolc, Hubert and Blachut, Krzysztof and Kryjak, Tomasz},
     year = {2020},
     series = {Computer Vision and Graphics : International Conference : ICCVG~2020 : Warsaw, Poland, September 14–16, 2020 : proceedings},
     pages = {151–163},
     doi = {10.1007/978-3-030-59006-2_14},
     collection = {Computer Vision and Graphics : International Conference : ICCVG~2020 : Warsaw, Poland, September 14–16, 2020 : proceedings},
   }