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Magdalena Szuflita-Żurawska
PeopleHead of the Scientific and Technical Information Services at the Gdansk University of Technology Library and the Leader of the Open Science Competence Center. She is also a Plenipotentiary of the Rector of the Gdańsk University of Technology for open science. She is a PhD Candidate. Her main areas of research and interests include research productivity, motivation, management of HEs, Open Access, Open Research Data, information...
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Student model representation for pedagogical virtual mentors
PublicationThe paper concerns technological aspects of virtual mentors construction, especially concentrating on the student model representation. The article distinguishes several types of information that is gathered by the pedagogical agents and other educational platforms, including student knowledge model, student progress tracking, interaction process patterns and learner preferences. A set of technologies used for the student model...
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The CDIO model in architectural education and research by design
PublicationArchitectural education has always been related to experimentation: that is, defining concepts, drawing sketches, working on models, then testing and modifying them. This activity mirrors the CDIO learning methods and objectives. Despite this, research studies into the applicability of the CDIO model in architectural curricula are scarce. In the discipline of architecture, hands-on experiences are associated not only with one of...
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Internet w procesie kształcenia studentów
PublicationWirtualna rzeczywistość sieci komputerowych staje się coraz bardziej obecna w naszym życiu. Internet odgrywa rosnącą rolę w edukacji, rekrutacji, handlu, sprawowaniu władzy oraz rozrywce. Dlatego też zastanowić się trzeba, na jakie problemy napotykają wykładowcy przy tworzeniu materiałów dostępnych przez Internet oraz studenci w związku z wykorzystaniem nowoczesnych technologii do pozyskiwania informacji i wiedzy....
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Computing methods for fast and precise body surface area estimation of selected body parts
PublicationCurrently used body surface area (BSA) formulas give satisfactory results only for individuals with typical physique, while for elderly, obese or anorectic people accurate results cannot be expected. Particularly noteworthy are the results for individuals with severe obesity (body-mass index greater than 35 kg/m2), for which BSA estimation errors reached 80%. The main goal of our study is the development of precise BSA models for...
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublicationA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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Dynamic Bankruptcy Prediction Models for European Enterprises
PublicationThis manuscript is devoted to the issue of forecasting corporate bankruptcy. Determining a firm’s bankruptcy risk is one of the most interesting topics for investors and decision-makers. The aim of the paper is to develop and to evaluate dynamic bankruptcy prediction models for European enterprises. To conduct this objective, four forecasting models are developed with the use of four different methods—fuzzy sets, recurrent and...
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Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublicationThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
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Applying Decisional DNA to Internet of Things: The Concept and Initial Case Study
PublicationIn this article, we present a novel approach utilizing Decisional DNA to help the Internet of Things capture decisional events and reuse them for decision making in future operations. The Decisional DNA is a domain-independent, standard and flexible knowledge representation structure that allows its domains to acquire, store, and share experiential knowledge and formal decision events in an explicit way. We apply this approach...
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Good practices in requirements, project and risk managment in educational IT projects
PublicationOne can find many learning aids and simulations of physical phenomena on the market - provided as a standalone application or as part of an educational package. However, only a few of them allow for the building of interactive experiments: experiments similar to those that should be conducted in physics laboratories at schools. Gdańsk University of Technology decided to fill this market niche by designing and constructing a set...
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E-experiments in physics. Proper business process management, collaborative development process and project management guidance – remedy for avoiding the main IT project’s failure
PublicationOnly a few of learning aids and simulations of physical phenomena allow for building interactive experiments; experiments similar to those that should be conducted in physics laboratories at schools. Group of staff from Gdansk University of Technology decided to fill this market niche by designing and constructing a set of virtual experiments – so called e-experiments. To avoid common problems that a lot of IT products brought...
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Bayesian Optimization for solving high-frequency passive component design problems
PublicationIn this paper, the performance of the Bayesian Optimization (BO) technique applied to various problems of microwave engineering is studied. Bayesian optimization is a novel, non-deterministic, global optimization scheme that uses machine learning to solve complex optimization problems. However, each new optimization scheme needs to be evaluated to find its best application niche, as there is no universal technique that suits all...
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Analysis of Factors Influencing the Prices of Tourist Offers
PublicationTourism is a significant branch of many world economies. Many factors influence the volume of tourist traffic and the prices of trips. There are factors that clearly affect tourism, such as COVID-19. The paper describes the methods of machine learning and process mining that allow for assessing the impact of various factors (micro, mezzo and macro) on the prices of tourist offers. The methods were used on large sets of real data...
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Sensors and Sensor’s Fusion in Autonomous Vehicles
PublicationAutonomous vehicle navigation has been at the center of several major developments, both in civilian and defense applications. New technologies such as multisensory data fusion, big data processing, and deep learning are changing the quality of areas of applications, improving the sensors and systems used. New ideas such as 3D radar, 3D sonar, LiDAR, and others are based on autonomous vehicle revolutionary development. The Special...
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Mispronunciation Detection in Non-Native (L2) English with Uncertainty Modeling
PublicationA common approach to the automatic detection of mispronunciation in language learning is to recognize the phonemes produced by a student and compare it to the expected pronunciation of a native speaker. This approach makes two simplifying assumptions: a) phonemes can be recognized from speech with high accuracy, b) there is a single correct way for a sentence to be pronounced. These assumptions do not always hold, which can result...
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Leveraging spatio-temporal features for joint deblurring and segmentation of instruments in dental video microscopy
PublicationIn dentistry, microscopes have become indispensable optical devices for high-quality treatment and micro-invasive surgery, especially in the field of endodontics. Recent machine vision advances enable more advanced, real-time applications including but not limited to dental video deblurring and workflow analysis through relevant metadata obtained by instrument motion trajectories. To this end, the proposed work addresses dental...
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Methodology for hospital design in architectural education
PublicationThe architecture of a hospital should be a response to strong user requirements. Recommendations on how to shape the environment of such facilities are highly complex, integrating guidelines from many fields of science. If contradictions between them exist, the designer is required to set priorities for spatial activities. This issue is particularly important during architectural education. The learning process should include projects...
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Scenario-planning solutions for waterfront flood-prone areas
PublicationThe aim of this article is to discuss the potential of applying scenario planning to achieve resilient and future-oriented solutions for flood-prone areas. The authors have proposed additions to scenario-planning processes based on the introduction of research-by-design architectural inquiries. Examined in this article is the insight into the testing of such a modified scenario-planning methodology during two courses that accompanied...
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Classification of Sea Going Vessels Properties Using SAR Satellite Images
PublicationThe aim of the project was to analyze the possibility of using machine learning and computer vision to identify (indicate the location) of all sea-going vessels located in the selected area of the open sea and to classify the main attributes of the vessel. The key elements of the project were to download data from the Sentinel-1 satellite [1], download data on the sea vessels [2], then automatically tag data and develop a detection...
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The evolution of education spaces - from plan as generator to regenerative architecture, virtual rooms and green campuses
PublicationThe study programmes are often considered the main formative factors in the process of educating future architects. Another highly influential component is the architectural characteristics of learning spaces, and consequently the impact of the physical built environment on the quality of education has been widely discussed. However, not often do we realise that the characteristics of education spaces correlate with the organisational...
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TeleCAD w kształceniu studentów Wydziału Inżynierii Lądowej Politechniki Gdańskiej
PublicationPrzedstawiono system TeleCAD opracowany w ramach projektu Leonardo da Vinci - Teleworkers Training for CAD Systems Users (1998-2001). Głównym celem projektu było stworzenie środowiska obsługi kursów programu AutoCAD bazującego na Internecie jako medium do komunikacji między uczestnikami oraz do dostarczania materiałów kursowych. W artykule zaprezentowano również system służący do oceny jakości szkoleń na odległość. Szkolenie TeleCAD...
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SkinDepth - synthetic 3D skin lesion database
Open Research DataSkinDepth is the first synthetic 3D skin lesion database. The release of SkinDepth dataset intends to contribute to the development of algorithms for:
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Karol Dziedziul dr hab.
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Diploma Seminar (PG_00042079) D&PE 2023 Winter Semester
e-Learning CoursesPresentation of the topic, the main issues of the diploma thesis and the tasks of the diploma thesis completed so far. The topic of the presentation is the same as the topic of the diploma thesis. Presentation of a literature analysis, including, among others: 10 papers from journals related to the topic of the work. Submitting to e-learning platform: - pdf version of the presentation - printed description (max 4 pages) a of the...
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METHODS OF TEACHING NOISE PROTECTION AT ENVIRONMENTAL ENGINEERING
PublicationNoise strongly influences both our health and behavior in everyday life and as employees or employers. The lost of hearing and other effects of noise on humans result not only in a significant decrease in the quality of life or work efficiency but have also have economic consequences. As noise can be preventable in part by the Environmental Engineers, but it is necessary to introduce them noise issues during their education process....
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Implementing artificial intelligence in forecasting the risk of personal bankruptcies in Poland and Taiwan
PublicationResearch background: The global financial crisis from 2007 to 2012, the COVID-19 pandemic, and the current war in Ukraine have dramatically increased the risk of consumer bankruptcies worldwide. All three crises negatively impact the financial situation of households due to increased interest rates, inflation rates, volatile exchange rates, and other significant macroeconomic factors. Financial difficulties may arise when the...
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Koncepcja systemu wspomagania decyzji nawigatora statku opartego na ewolucyjnym planowaniu manewrów antykolizyjnych
PublicationArtykuł przedstawia koncepcję systemu wspomagania decyzji nawigatora statku opartego na wątkach badań prowadzonych wcześniej przez autora. System będzie rozszerzał funkcjonalność systemów dotychczasowych o możliwość szczegółowego planowania bezpiecznej trajektorii statku na wodach zamkniętych, z dużą liczbą statków obcych i ograniczeniami toru wodnego. Artykuł zawiera dyskusję możliwych podejść do planowania manewrów, optymalizacji...
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СИЛОВОЙ ПРЕОБРАЗОВАТЕЛЬ С АКТИВНЫМ ПОДАВЛЕНИЕМ ВЫСШИХ ГАРМОНИК ДЛЯ СИСТЕМ ЭЛЕКТРОСНАБЖЕНИЯ ЛЕТАТЕЛЬНЫХ АППАРАТОВ (Power converter with active suppression of higher harmonics for aircraft power supply systems)
PublicationПредставлены два алгоритма активной фильтрации для силового преобразователя с активным подавлением высших гармоник. Первый алгоритм основан на дискретном преобразовании Фурье: посредством синтезированной системы управления инвертированные измеренные высшие гармоники напряжения поступают на вход инвертора. Второй метод управления основан на алгоритме с использованием принципов самообучения, что значительно снижает потребность в...
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Szymon Kowalski mgr inż. arch.
PeopleResearch assistant in architectural studies of medieval and modern architecture in the Baltic Sea region. Scientifically, studies the possibilities of implementing virtual reality technology in the context of the conservation of architectural monuments and its impact on the theory of conservation, as well as the solutions for increasing the learning capabilities of architecture students.
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Listening to Live Music: Life beyond Music Recommendation Systems
PublicationThis paper presents first a short review on music recommendation systems based on social collaborative filtering. A dictionary of terms related to music recommendation systems, such as music information retrieval (MIR), Query-by-Example (QBE), Query-by-Category (QBC), music content, music annotating, music tagging, bridging the semantic gap in music domain, etc. is introduced. Bases of music recommender systems are shortly presented,...
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Universities as Part of the Urban Transport System—Analysis Using the Example of the Gdansk University of Technology and Medical University of Gdansk
PublicationMany cities perceive academic function as a distinctive feature, representing the rank and prestige of the city. Universities provide places for work and learning for a high number of people and represent a significant proportion compared to the total city population (even 22%). Many of Polish universities are located in the urban structure in the form of spatially concentrated campuses, where the number of people working and studying...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublicationIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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Comparing the Effectiveness of ANNs and SVMs in Forecasting the Impact of Traffic-Induced Vibrations on Building
PublicationTraffic - induced vibrations may cause damage to structural elements and may even lead to structural collapse. The aim of the article is to compare the effectiveness of algorithms in forecasting the impact of vibrations on buildings using the Machine Learning (ML) methods. The paper presents two alternative approaches by using Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). Factors that may affect traffic-induced...
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Method of selecting the LS-SVM algorithm parameters in gas detection process
PublicationIn this paper we showed the method of resistive gas sensors data processing. The UV irradiation and temperature modulation was applied to improve gas sensors’ selectivity and sensitivity. Noise voltage across the sensor’s terminals (proportional to its resistance fluctuations) was recorded to estimate power spectral density. This function was an input data vector for LS-SVM (least squares – support vector machine) algorithm, which...
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Qualia: About Personal Emotions Representing Temporal Form of Impressions - Implementation Hypothesis and Application Example
PublicationThe aim of this article is to present the new extension of the xEmotion system as a computerized emotional system, part of an Intelligent System of Decision making (ISD) that combines the theories of affective psychology and philosophy of mind. At the same time, the authors try to find a practical impulse or evidence for a general reflection on the treatment of emotions as transitional states, which at some point may lead to the...
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Technique for reducing erosion in large-scale circulating fluidized bed units
PublicationThis paper presents a methodology, implemented for a real industrial-scale circulating fluidized bed boiler, to mitigate the risk of heating surfaces exposed to an intensive particle erosion process. For this purpose, a machine learning algorithm was developed to support the boiler reliability management process. Having a tool that can help mitigate the risk of uncontrolled power unit failure without expensive and technically complex...
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublicationDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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IFE: NN-aided Instantaneous Pitch Estimation
PublicationPitch estimation is still an open issue in contemporary signal processing research. Nowadays, growing momentum of machine learning techniques application in the data-driven society allows for tackling this problem from a new perspective. This work leverages such an opportunity to propose a refined Instantaneous Frequency and power based pitch Estimator method called IFE. It incorporates deep neural network based pitch estimation...
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Keystroke Dynamics Patterns While Writing Positive and Negative Opinions
PublicationThis paper deals with analysis of behavioural patterns in human–computer interaction. In the study, keystroke dynamics were analysed while participants were writing positive and negative opinions. A semi-experiment with 50 participants was performed. The participants were asked to recall the most negative and positive learning experiences (subject and teacher) and write an opinion about it. Keystroke dynamics were captured and...
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Is This Distance Teaching Planning That Bad?
PublicationIn spring 2020, university courses were moved into the virtual space due to the Covid-19 lockdown. In this paper, we use experience from courses at Gdańsk University of Technology and ETH Zurich to identify core problems in distance teaching planning and to discuss what to do and what not to do in teaching planning after the pandemic. We conclude that we will not return to the state of (teaching) affairs that we had previously....
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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublicationThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
PublicationThis paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...
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Monitoring the BTEX Volatiles during 3D Printing with Acrylonitrile Butadiene Styrene (ABS) Using Electronic Nose and Proton Transfer Reaction Mass Spectrometry
PublicationWe describe a concept study in which the changes of concentration of benzene, toluene, ethylbenzene, and xylene (BTEX) compounds and styrene within a 3D printer enclosure during printing with different acrylonitrile butadiene styrene (ABS) filaments were monitored in real-time using a proton transfer reaction mass spectrometer and an electronic nose. The quantitative data on the concentration of the BTEX compounds, in particular...
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Anna Czaja mgr inż.
PeopleAfter completing Master's studies in Computer Science (Gdansk University of Technology, Faculty of Electronics, Telecommunications and Informatics), she worked as a programmer for several years. Currently employed as an assistant at the Department of Applied Informatics in Management (Gdańsk University of Technology, Faculty of Management and Economics). Participant in third degree doctoral studies at the Faculty of Management...
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Leszek Ziemczonek dr
PeopleUniversity education 1973-1978 – Nicolaus Copernicus University in Toruń, University of Gdańsk in Gdańsk, Mathematical Physics, M. Sc. 1979 – Diploma of Postgraduate Studies, Pedagogics 1989 – Institute of Physics, Polish Academy of Sciences in Warsaw, Theoretical Physics, Ph. D. 2010-2012 – Diploma of Postgraduate Studies, Mathematics Training: · 09.1983 – Trieste (Italy) – International Centre for Theoretical Physics...
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Experimental and Theoretical Insights into the Intermolecular Interactions in Saturated Systems of Dapsone in Conventional and Deep Eutectic Solvents
PublicationSolubility is not only a crucial physicochemical property for laboratory practice but also provides valuable insight into the mechanism of saturated system organization, as a measure of the interplay between various intermolecular interactions. The importance of these data cannot be overstated, particularly when dealing with active pharmaceutical ingredients (APIs), such as dapsone. It is a commonly used anti-inflammatory and...
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Nadzeya Sabatini dr
PeopleNadzeya Sabatini is Assistant Professor in Digital Transformation at Gdańsk University of Technology (Gdansk, Poland), its Department of Informatics in Management (Faculty of Management and Economics). Nadzeya is lecturer at USI – Università della Svizzera italiana (Lugano, Switzerland), a research fellow at the Institute of Digital Technologies for Communication of the same university, and coordinator of MSc in Digital Fashion...
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Magdalena Maria Łapińska dr inż.
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Oferta kształcenia a wymogi współczesnego rynku pracy
PublicationWspółcześnie zmianom ulegają struktury gospodarek oraz sposoby gospodarowania poszczególnymi zasobami na rynkach. Wpływ na to mają nowoczesne technologie, procesy globalizacji i integracji. Obserwowane dynamiczne zmiany wymuszają włączenie się w proces unowocześniania różnych uczestników rynku. Jednym z nich są instytucje zajmujące się szeroko rozumianym kształceniem, które przygotowują zasoby pracy do wejścia na rynek pracy. Celem...
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A Triplet-Learnt Coarse-to-Fine Reranking for Vehicle Re-identification
PublicationVehicle re-identification refers to the task of matching the same query vehicle across non-overlapping cameras and diverse viewpoints. Research interest on the field emerged with intelligent transportation systems and the necessity for public security maintenance. Compared to person, vehicle re-identification is more intricate, facing the challenges of lower intra-class and higher inter-class similarities. Motivated by deep...