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47th International Conference on Telecommunications and Signal Processing, TSP 2024

作者： Bugarinović, Željko Gavrilović, Milan Ristić, Aleksandar Bugarinović, Milka Šarkanović Radulović, Aleksandra Govedarica, Miro University of Novi Sad Faculty of Technical Sciences Department for Computing and Control Engineering Trg Dositeja Obradovića 6 Novi Sad Serbia

ISBN: (纸本)9798350365597

This paper analyzes the application of the YOLO algorithm to automatically recognize hyperbolic reflections on radargrams. A specific shape of hyperbolic reflection on radargrams occurs with objects of circular cross-section that are scanned perpendicular to their axis, such as underground pipes. Requirements for processing a large number of radargrams are increasingly being imposed in practice. Therefore, the development of algorithms for the automated finding of hyperbolic reflections on radargrams has been intensified in recent years. Conventional methods take a lot of time and are more susceptible to noise than algorithms based on deep learning. One of such algorithms is also applied in this paper. The model was trained with 2000 synthetic radargrams generated using gprMax software. The basic idea is reflected in the analysis of the successful detection of hyperbolic reflections on real radargrams using a model trained only with synthetic radargrams. Experimental results show a high level of success. © 2024 IEEE.

关键词： Ground penetrating radar systems

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Magnetic Flux Servoing for Precise Localization Based on Gradient Tensor Contractions 19

Magnetic Flux Servoing for Precise Localization Based on Gra...

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19th IEEE International Conference on Automation Science and Engineering, CASE 2023

作者： Martinovic, Dean Orsag, Matko University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems Zagreb10000 Croatia

ISBN: (纸本)9798350320695

This paper focuses on bridge inspections performed by intelligent unmanned aerial vehicles (UAV). For this, small data loggers are placed by the UAVs at the bridge, which have to be removed later. In our previous work we presented the magnetic localization method SRIOD, which not only detects the center of the data logger but also its orientation. In this work we proof SRIOD in a real application and let a robotic arm locate a magnetic target. The hardware involved is presented including the control strategy for the robot. The motions of the robot and the magnetic target are captured with 12 Optitrack cameras in order to validate the localization quality. © 2023 IEEE.

关键词： Antennas

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A New Benchmark and Algorithm for Clothes-Changing Video Person Re-Identification

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IEEE Transactions on Information Forensics and Security 2025年 20卷 1993-2005页

作者： Wang, Likai Zhang, Xiangqun Han, Ruize Wei, Yanjie Wang, Song Feng, Wei Tianjin University College of Intelligence and Computing Tianjin300350 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518107 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

Person re-identification (Re-ID) is a classical computer vision task and has significant applications for public security and information forensics. Recently, long-term Re-ID with clothes-changing has attracted increasing attention. However, existing methods mainly focus on image-based setting, where richer temporal information is overlooked. In this paper, we focus on the relatively new yet practical problem of Clothes-Changing Video-based Re-ID (CCVReID), which is less studied. First, given the dataset shortage, we build two new benchmark datasets for CCVReID problem, including a large-scale synthetic video dataset and a real-world one, both containing human sequences with various clothing changes. Moreover, we systematically study this problem by simultaneously considering the classical appearance feature and temporal feature contained in the video. We develop a dual-branch fusion framework that makes use of the information from both clothes-aware appearance feature and clothes-free gait feature. For better information fusion, a confidence-guided re-ranking strategy is proposed to adaptively balance the weight of these two categories of features. We have released the benchmark and code proposed in this work to the public at https://***/kkw98/CCVReID. © 2025 IEEE.

关键词： Reamers

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Position Paper: Enhancing the Learning and Mastery of Academic Writing in the Serbian Language Through an AI Tool with Adaptive Scaffolding 17

Position Paper: Enhancing the Learning and Mastery of Academ...

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17th International Conference on Computer Supported Education, CSEDU 2025

作者： Francišković, Teodor Sakal Gajić, Dušan Luburić, Nikola Slivka, Jelena Department of Computing and Control Engineering Faculty of Technical Sciences University of Novi Sad Trg Dositeja Obradovića 6 Novi Sad Serbia

ISBN: (纸本)9789897587467

Academic writing is a significant challenge for many learners striving for proficiency. Adaptive scaffolding techniques and AI tools in education have proven effective in addressing this challenge and supporting learners in improving their academic writing skills when used correctly. This position paper proposes combining adaptive scaffolding techniques with AI tools in a public university's final year academic writing course to enhance the learning experience and mastery of academic writing skills in Serbian. The proposed plan outlines the course structure and details how the AI-driven adaptive scaffolding techniques will be integrated to support the learning experience, focusing on summative and formative feedback from the AI tool. The proposed plan is a work in progress. It will be implemented in the next iteration of the course for evaluation, taking into account potential counter-arguments and their impact on the tool's development and the student's learning experience and outcomes. This study will analyse our plan's effectiveness in enhancing the learning experience and outcomes. The expected outcome is to assist students in their learning while contributing to the development of AI in education and the Serbian language. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Students

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4K Video Coding Efficiency in UAV Systems 45

4K Video Coding Efficiency in UAV Systems

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45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022

作者： Benjak, J. Hofman, D. Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Zagreb Croatia

ISBN: (纸本)9789532331035

With increasing requirements for high quality, low bandwidth video transmission systems, comes a demand for more ad hoc video encoders. Unmanned Aerial Vehicles (UAVs), or just drones, have recently grown in popularity and use. Therefore, in this paper, we provide an efficiency comparison of the two most popular video encoders in a First-person view (FPV) drone piloting system. We film all the test sequences ourselves, using a drone with an attached 4K camera. Each sequence captures a scene with different spatiotemporal characteristics. Because video encoders are sensitive to video content or scene complexity, instead of doing a comprehensive comparison of all sequences at once, we first classify all the sequences into four groups. Finally, we examine the compression efficiency by varying the parameters with the highest impact on encoder operation. The quality of compressed footage is determined using four objective video quality measures. Due to high computational complexity, tests were performed on several nodes of a supercomputer and the relative encoding times were also considered. © 2022 Croatian Society MIPRO.

关键词： Antennas

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Smooth Motion Planning of an Omnidirectional Mobile Robot in Dynamic Environments

Smooth Motion Planning of an Omnidirectional Mobile Robot in...

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2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2022

作者： Šelek, Ana Seder, Marija Department of Control and Computer Engineering Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

In this paper, a real-time smooth motion planning method for a four mecanum wheeled omnidirectional mobile robot in dynamic environments that generates a smooth collision-free trajectory is proposed. The method employs a graph-search-based path planning algorithm and a smoothing technique based on clothoids. It is suitable for real-time operation due to its computational simplicity and allows fast path replanning in case the robot encounters unknown and dynamic obstacles. Such a path is feasible for holonomic mobile robots since it does not contain sharp turns so the energy consumption is reduced. Our method is compared to the reactive model predictive control scheme in simulations. The comparison showed advantages of the proposed method in the reduced task execution time, path length, cumulative replanning time, and smooth velocity profile. © 2022 IEEE.

关键词： Motion planning

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Synergistically Learning Class-specific Tokens for Multi-class Whole Slide Image Classification

Synergistically Learning Class-specific Tokens for Multi-cla...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Sun, Pengzhong Wang, Wei Li, Xiangyu Dong, Suyu Li, Shuo Wang, Kuanquan Luo, Gongning Harbin Institute of Technology Faculty of Computing Harbin China Harbin Institute of Technology Faculty of Computing Shenzhen China Northeast Forestry University College of Computer and Control Engineering Harbin China Case Western Reserve University Case School of Engineering Cleveland United States

ISBN: (纸本)9798350337488

The application of transformer architecture in analyzing whole slide images (WSIs) has become increasingly popular due to its remarkable ability to learn complex associations. Nevertheless, a significant drawback emerges in the multiclass analysis of WSIs. The majority of the transformer-based methods available currently rely primarily on a single, class-agnostic token. This approach might not ideally capture the subtleties of class-discriminative information. To address this challenge, we present an innovative approach tailored for multi-class WSI analysis that harnesses the power of class-specific tokens. Central to our method is a novel attention mechanism designed to foster a synergistic learning relationship between patch and class tokens, enhancing the granularity of information captured and ensuring a more comprehensive representation of the WSI. Complementing this, we introduce a dynamic class-centric training strategy designed to optimize token representation learning, ensuring each token is informatively aligned with its corresponding class. Through extensive experimentation on three challenging multi-class WSI analysis datasets, our method consistently demonstrates superior performance, underscoring its potential as a robust solution for multi-class WSI analysis tasks. © 2023 IEEE.

关键词： Multi-class whole slide image analysis Multiple instance learning Transformer

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Brain over Brawn: Using a Stereo Camera to Detect, Track, and Intercept a Faster UAV by Reconstructing the Intruder's Trajectory

Field Robotics

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Field Robotics 2025年 2卷 222-240页

作者： Antonella Barišić Frano Petric Stjepan Bogdan Laboratory for Robotics and Intelligent Control Systems Faculty of Electrical Engineering and Computing University of Zagreb Unska 3 Zagreb Croatia

This paper presents our approach to intercepting a faster intruder UAV, inspired by the MBZIRC 2020 Challenge 1. By utilizing a priori knowledge of the shape of the intruder's trajectory, we can calculate an interception point. Target tracking is based on image processing by a YOLOv3 Tiny convolutional neural network, combined with depth calculation using a gimbal-mounted ZED Mini stereo camera. We use RGB and depth data from the camera, devising a noise-reducing histogram-filter to extract the target's 3D position. Obtained 3D measurements of target's position are used to calculate the position, orientation, and size of a figure-eight shaped trajectory, which we approximate using a Bernoulli lemniscate. Once the approximation is deemed sufficiently precise, as measured by the distance between observations and estimate, we calculate an interception point to position the interceptor UAV directly on the intruder's path. Our method, which we have significantly improved based on the experience gathered during the MBZIRC competition, has been validated in simulation and through field experiments. Our results confirm that we have developed an efficient, visual-perception module that can extract information describing the intruder UAV's motion with precision sufficient to support interception planning. In a majority of our simulated encounters, we can track and intercept a target that moves 30% faster than the interceptor. Corresponding tests in an unstructured environment yielded 9 out of 12 successful results.

关键词： Autonomous aerial vehicles Trajectory Target tracking Cameras Three-dimensional displays Robots Radar tracking Image reconstruction Estimation Detectors

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Improving Lane Annotation in Autonomous Driving Data Sets with Classical Computer Vision Techniques

Improving Lane Annotation in Autonomous Driving Data Sets wi...

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2023 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2023

作者： Stojanovic, Dimitrije Cetic, Nenad Kocic, Jelena Pavkovic, Bogdan University of Novi Sad Faculty of Technical Sciences Departmant of Computing and Control Engineering Novi Sad Serbia Customer Programs TTTech Auto Belgrade Serbia

ISBN: (纸本)9798350347722

Autonomous driving systems rely on accurate and reliable lane detection to safely navigate roads. In this paper, we propose a method for improving lane annotation in autonomous driving data sets using classical computer vision techniques. The proposed method combines the Hough transform and linear curve fitting to detect and smooth the positions of lane markings in a video stream. We evaluate the performance of the proposed method on the Berkeley DeepDrive (BDD) dataset and compare it to the ground truth annotations. Results show that the proposed method achieves a high level of accuracy and robustness in lane detection, and can effectively improve lane annotation in autonomous driving data sets. Our method provides a valuable tool for training and evaluating autonomous driving systems, and can also be applied to improve annotation in different datasets. © 2023 IEEE.

关键词： Hough transforms

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Autonomous, Mobile Manipulation in a Wall-Building Scenario: Team LARICS at MBZIRC 2020

Field Robotics

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Field Robotics 2025年 2卷 201-221页

作者： Ivo Vatavuk Marsela Polic Ivan Hrabar Frano Petric Matko Orsag Stjepan Bogdan Laboratory for Robotics and Intelligent Control systems University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 Zagreb Croatia

In this paper we present our hardware design and control approaches for a mobile manipulation platform used in Challenge 2 of the MBZIRC 2020 competition. In this challenge, a team of UAVs and a single UGV collaborate in an autonomous, wall-building scenario, motivated by construction automation and large-scale robotic 3D printing. The robots must be able, autonomously, to detect, manipulate, and transport bricks in an unstructured, outdoor environment. Our control approach is based on a state machine that dictates which controllers are active at each stage of the Challenge. In the first stage our UGV uses visual servoing and local controllers to approach the target object without considering its orientation. The second stage consists of detecting the object's global pose using OpenCV-based processing of RGB-D image and point-cloud data, and calculating an alignment goal within a global map. The map is built with Google Cartographer and is based on onboard LIDAR, IMU, and GPS data. Motion control in the second stage is realized using the ROS Move Base package with Time-Elastic Band trajectory optimization. Visual servo algorithms guide the vehicle in local object-approach movement and the arm in manipulating bricks. To ensure a stable grasp of the brick's magnetic patch, we developed a passively-compliant, electromagnetic gripper with tactile feedback. Our fully-autonomous UGV performed well in Challenge 2 and in post-competition evaluations of its brick pick-and-place algorithms.

关键词： Robots Robot kinematics Navigation Manipulators Cameras Buildings Grippers Automation Service robots Laser radar

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