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Wyniki wyszukiwania dla: VEHICLE DETECTION, TRAFFIC MONITORING SYSTEM, BACKGROUND SUBTRACTION, CONVOLUTIONAL NEURAL NETWORK
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Neural Architecture Search for Skin Lesion Classification
PublikacjaDeep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture. This is a tedious and time-consuming process that requires expert knowledge. Different tasks need very different architectures to obtain satisfactory results. The group of methods called the neural architecture search (NAS) helps to find effective architecture...
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Research on Quality Requirements of Data Transmission Services in RSMAD
PublikacjaThe paper presents a results and analysis of research of the quality of service requirements (defined by the QoS attributes) for imaging data transmission services using Radio System for Monitoring and Acquisition of Data from Traffic Enforcement Cameras (in short RSMAD). The paper also presents and discusses results of test on the impact of the size of photos from traffic enforcement cameras on the average transmission time. These...
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User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
PublikacjaIn this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...
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OOA-modified Bi-LSTM network: An effective intrusion detection framework for IoT systems
PublikacjaCurrently, the Internet of Things (IoT) generates a huge amount of traffic data in communication and information technology. The diversification and integration of IoT applications and terminals make IoT vulnerable to intrusion attacks. Therefore, it is necessary to develop an efficient Intrusion Detection System (IDS) that guarantees the reliability, integrity, and security of IoT systems. The detection of intrusion is considered...
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An application of acoustic sensors for the monitoring of road traffic
PublikacjaAssessment of road traffic parameters for the developed intelligent speed limit setting decision system constitutes the subject addressed in the paper. Current traffic conditions providing vital data source for the calculation of the locally fitted speed limits are assessed employing an economical embedded platform placed at the roadside. The use of the developed platform employing a low-powered processing unit with a set of microphones,...
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Zastosowanie sieci neuronowych do detekcji impulsów o znanym kształcie w obecności silnego szumu i trendu
PublikacjaDetekcja impulsów w odebranym sygnale radiowym, zwłaszcza w obecności silnego szumu oraz trendu, jest trudnym zadaniem. Artykuł przedstawia propozycje rozwiązań wykorzystujących sieci neuronowe do detekcji impulsów o znanym kształcie w obecności silnego szumu i trendu. Na potrzeby realizacji tego zadania zaproponowano dwie architektury. W pracy przedstawiono wyniki badań wpływu kształtu impulsu, mocy zakłóceń szumowych oraz trendu...
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Quality Parameters in IMS/NGN Networks
PublikacjaThe Next Generation Network (NGN) architecture, including elements of the IP Multimedia Subsystem (IMS) concept, is a proposition of a telecommunication network dedicated to the needs of current and future information society. The main goal of NGN is to provide Quality of Service (QoS), for which proper network design is necessary with respect to among others standardized call processing performance parameters, including expected...
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Performance Evaluation of Selected Parallel Object Detection and Tracking Algorithms on an Embedded GPU Platform
PublikacjaPerformance evaluation of selected complex video processing algorithms, implemented on a parallel, embedded GPU platform Tegra X1, is presented. Three algorithms were chosen for evaluation: a GMM-based object detection algorithm, a particle filter tracking algorithm and an optical flow based algorithm devoted to people counting in a crowd flow. The choice of these algorithms was based on their computational complexity and parallel...
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Impact of Visual Image Quality on Lymphocyte Detection Using YOLOv5 and RetinaNet Algorithms
PublikacjaLymphocytes, a type of leukocytes, play a vital role in the immune system. The precise quantification, spatial arrangement and phenotypic characterization of lymphocytes within haematological or histopathological images can serve as a diagnostic indicator of a particular lesion. Artificial neural networks, employed for the detection of lymphocytes, not only can provide support to the work of histopathologists but also enable better...
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Selective monitoring of noise emitted by vehicles involved in road traffic
PublikacjaAn acoustic intensity probe was developed measures the sound intensity in three orthogonal directions, making possible to calculate the azimuth and elevation angles, describing the sound source position. The acoustic sensor is made in the form of a cube with a side of 10 mm, on the inner surfaces of which the digital MEMS microphones are mounted. The algorithm works in two stages. The first stage is based on the analysis of sound...
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Architektury klasyfikatorów obrazów
PublikacjaKlasyfikacja obrazów jest zagadnieniem z dziedziny widzenia komputerowego. Polega na całościowej analizie obrazu i przypisaniu go do jednej lub wielu kategorii (klas). Współczesne rozwiązania tego problemu są w znacznej części realizowane z wykorzystaniem konwolucyjnych głębokich sieci neuronowych (convolutional neural network, CNN). W tym rozdziale opisano przełomowe architektury CNN oraz ewolucję state-of-the-art w klasyfikacji...
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Performance Analysis of Convolutional Neural Networks on Embedded Systems
PublikacjaMachine learning is no longer confined to cloud and high-end server systems and has been successfully deployed on devices that are part of Internet of Things. This paper presents the analysis of performance of convolutional neural networks deployed on an ARM microcontroller. Inference time is measured for different core frequencies, with and without DSP instructions and disabled access to cache. Networks use both real-valued and...
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Self-Organizing Wireless Monitoring System for Containers
PublikacjaThis paper presents a description of new global monitoring system for containers, with its layer-modular structure, as a solution for enhance security and efficiency of container transport with particular emphasis on the practical implementation of that system for maritime container terminals. Especially the Smart Container Module (SCM) architecture and its operation as a part of the Self-Organizing Container Monitoring Network...
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Parallel Background Subtraction in Video Streams Using OpenCL on GPU Platforms
PublikacjaImplementation of the background subtraction algorithm using OpenCL platform is presented. The algorithm processes live stream of video frames from the surveillance camera in on-line mode. Processing is performed using a host machine and a parallel computing device. The work focuses on optimizing an OpenCL algorithm implementation for GPU devices by taking into account specific features of the GPU architecture, such as memory access,...
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Viewpoint independent shape-based object classification for video surveillance
PublikacjaA method for shape based object classification is presented.Unlike object dimension based methods it does not require any system calibration techniques. A number of 3D object models are utilized as a source of training dataset for a specified camera orientation. Usage of the 3D models allows to perform the dataset creation process semiautomatically. The background subtraction method is used for the purpose of detecting moving objects...
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The application of neural networks in forecasting the influence of traffic-induced vibrations on residential buildings
PublikacjaTraffic-induced vibrations may cause the cracking of plaster, damage to structural elements and, in extreme cases, may even lead to the structural collapse of residential buildings. The aim of this article is to analyse the effectiveness of a method of forecasting the impact of vibrations on residential buildings using the concept of artificial intelligence. The article presents several alternative forecasting systems for which...
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Novel proposal for V2X systems and WBAN cooperation to improve road safety
PublikacjaIn this paper, a novel proposal of the automotive Vehicle-to-Everything system solution is presented. In this proposal, there are included the Machine to Machine type communication system and the sensor system based on a short-range the Wireless Body Area Network communication. The aim of this paper is the analysis of the model for communication, especially its architecture and signals structure for the proposed solution. The use...
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Development of Intelligent Road Signs with V2X Interface for Adaptive Traffic Controlling
PublikacjaThe objective of this paper is to present a practical project of intelligent road signs, under which a series of new products for the regulation of traffic is being created. The engineering part of the project, described in this paper, was preceded by a series of experimental studies, the results of which were described in another paper accepted for publication at the MTS-ITS conference 2019, entitled "Comparative study on the effectiveness...
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A method of self-testing of analog circuits based on fully differential op-amps with theTCBF classifier
PublikacjaA new approach of self-testing of analog circuits based on fully differential op-amps of mixed-signal systems controlled by microcontrollers is presented. It consists of a measurement procedure and a fault diagnosis procedure. We measure voltage samples of a time response of a tested circuit on a stimulation of a unit step function given at the common-mode reference voltage input of the op-amp. The fault detection and fault localization...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublikacjaSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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Software modules and application layer's security structure of RSMAD
PublikacjaThe paper discusses the software modules of Radio System for Monitoring and Acquisition of Data from Traffic Enforcement Cameras (in short RSMAD). The structure of the application layer of the system has also been analysed in details, including: purpose, structure and principles of operation of software modules constituting this system. In addition, the paper presents and discusses the structure of security of application layer...
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The impact of the AC922 Architecture on Performance of Deep Neural Network Training
PublikacjaPractical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...
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Evaluation of sound event detection, classification and localization in the presence of background noise for acoustic surveillance of hazardous situations
PublikacjaAn evaluation of the sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for separating foreground events from the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the classifier...
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Extraction of stable foreground image regions for unattended luggage detection
PublikacjaA novel approach to detection of stationary objects in the video stream is presented. Stationary objects are these separated from the static background, but remaining motionless for a prolonged time. Extraction of stationary objects from images is useful in automatic detection of unattended luggage. The proposed algorithm is based on detection of image regions containing foreground image pixels having stable values in time and...
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Sound quality metrics applied to road noise evaluation
PublikacjaRoad noise monitoring systems typically measure sound levels in specific time periods. The more insightful approach suggests to measure also the nature of noise. Sound quality of sounds such as car noise can be objectively evaluated by several parameters. One of them is psychoacoustic annoyance, described by loudness, tone color, and the temporal structure of sound. In this paper the assessment of several sound quality parameters, such...
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Autoencoder application for anomaly detection in power consumption of lighting systems
PublikacjaDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
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Multimodal Surveillance Based Personal Protection System
PublikacjaA novel, multimodal approach for automatic detection of abduction of a protected individual, employing dedicated personal protection device and a city monitoring system is proposed and overviewed. The solution is based on combining four modalities (signals coming from: Bluetooth, fixed and PTZ cameras, thermal camera, acoustic sensors). The Bluetooth signal is used continuously to monitor the protected person presence, and in case...
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Sign Language Recognition Using Convolution Neural Networks
PublikacjaThe objective of this work was to provide an app that can automatically recognize hand gestures from the American Sign Language (ASL) on mobile devices. The app employs a model based on Convolutional Neural Network (CNN) for gesture classification. Various CNN architectures and optimization strategies suitable for devices with limited resources were examined. InceptionV3 and VGG-19 models exhibited negligibly higher accuracy than...
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Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters
PublikacjaSmart meters in road lighting systems create new opportunities for automatic diagnostics of undesirable phenomena such as lamp failures, schedule deviations, or energy theft from the power grid. Such a solution fits into the smart cities concept, where an adaptive lighting system creates new challenges with respect to the monitoring function. This article presents research results indicating the practical feasibility of real‐time...
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Reduction of road traffic noise by source measures — present and future strategies
PublikacjaThe current trend worldwide is less focused on reducing road traffic noise. This is in strong contrast to the severe impact of traffic noise to the general health and quality of life. A more holistic and combined strategy is needed. Current international rules and regulations regarding vehicles and tyres are not sufficient to reduce traffic noise levels in an effective way. Calculations show that these regulations will only yield...
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Development of a new generation of unmanned surface and underwater vehicles using the advanced technologies and achievements towards the application of control systems by the artificial intelligence AI.
PublikacjaThe operation of offshore structures at sea requires implementation of the advanced systems of permanent monitoring of work of such the installations. Novel solutions concerning such the systems should be associated with application of unmanned maritime surface and underwater platforms. The unmanned maritime platforms are and will be based on application of the newest achievements of some important technologies. Between these technologies...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublikacjaAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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Cascade Object Detection and Remote Sensing Object Detection Method Based on Trainable Activation Function
PublikacjaObject detection is an important process in surveillance system to locate objects and it is considered as major application in computer vision. The Convolution Neural Network (CNN) based models have been developed by many researchers for object detection to achieve higher performance. However, existing models have some limitations such as overfitting problem and lower efficiency in small object detection. Object detection in remote...
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An Approach to the Detection of Bank Robbery Acts Employing Thermal Image Analysis
PublikacjaA novel approach to the detection of selected security-related events in bank monitoring systems is presented. Thermal camera images are used for the detection of people in difficult lighting conditions. Next, the algorithm analyses movement of objects detected in thermal or standard monitoring cameras using a method evolved from the motion history images algorithm. At the same time, thermal images are analyzed in order to detect...
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XPS analysis of TBBO glass
Dane BadawczeGlasses and glass-ceramics with nominal composition 73 TeO2– 4BaO– 3Bi2O3–18SrF2-2RE2O3 (where RE = Eu, Dy) have been synthesized by conventional melt-quenching technique and subsequent heat treatment at 370 °C for 24 h in air atmosphere. Various Eu3+ to Dy3+ molar ratio have been applied to investigate luminescence properties in both glass and glass-ceramic...
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The Effects of Roadside Hazards on Road Accident Severity
PublikacjaThe risk of becoming involved in an accident emerges when elements of the transport system do not operate properly (man – vehicle – road – roadside). The road, its traffic layout andsafety equipment have a critical impact on road user safety. This gives infrastructural work a priority in road safety strategies and programmes. Run-off-road accidents continue to be one of the biggest problems of road safety with consequences including...
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Pomiarowa ocena efektywności systemu antyspoofingowego opartego na przetwarzaniu wieloantenowym
PublikacjaNiniejszy referat dotyczy problemu wykrywania i przeciwdziałania atakom typu spoofing w globalnych systemach nawigacji satelitarnej. Pierwsza część referatu stanowi wprowadzenie w temat spoofingu oraz przegląd sposobów jemu przeciwdziałania. Następnie, przedstawiono autorską koncepcję systemu antyspoofingowego opartego na przetwarzaniu wieloantenowym, a także opisano implementację prototypu tego systemu. Część trzecią poświęcono...
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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublikacjaThis paper contains research results of the diagnostics of induction motor bearings based on measurement of the supply current with usage of artificial neural networks. Bearing failure amount is greater than 40% of all engine failures, which makes their damage-free operation crucial. Tests were performed on motors with intentionally made bearings defects. Chapter 2 introduces the concept of artificial neural networks. It presents...
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Intelligent monitoring the vertical dynamics of wheeled inspection vehicles
PublikacjaThe problem of intelligent monitoring of the vertical dynamics of wheeled inspection vehicles is addressed. With the independent MacPherson suspension system installed, the basic analysis focuses on the evaluation of the parameters of the so-called quarter car model. To identify a physically motivated continuous description, in practice, dedicated integral-horizontal filters are used. The obtained discrete model, which retains...
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The networking of the justice system as part of public court networks
PublikacjaThe goal of this paper is to look at the organizational structure of the justice system and provide the answer to the basic question of the possible network relations, their force, and imapct. As part od the paper, I have defined public inetrorganisational court network, dividing them into regulatory inter-organisational networks nad voluntary inetrorganisational networks. Emphasis has also been placed on the benefits and threats...
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublikacjaThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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Aktywny system RFID do lokalizacji i identyfikacji obiektów w wielomodalnej infrastrukturze bezpieczeństwa
PublikacjaPrzedstawiono prace koncepcyjne, badawcze oraz implementacyjne skoncentrowane na praktycznej realizacji systemu detekcji obiektów z wykorzystaniem kamer wizyjnych i identyfikacji radiowej. Zaproponowano rozbudowę wielomodalnego teleinformatycznego systemu bezpieczeństwa o warstwę identyfikacji radiowej obiektów. Omówiono założenia zaprojektowanego systemu oraz opracowaną warstwę sprzętową. Zaproponowano i przedyskutowano praktyczne...
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Study of QoS Parameters Measurement Methodology and Requirements in RSMAD
PublikacjaThe paper presents the results of analysis and research of the quality of service requirements (defined by the QoS parameters) for data transmission services in Radio System for Monitoring and Acquisition of Data from Traffic Enforcement Cameras (in short: RSMAD). The paper also presents and discusses the results of test of impact of the size of images from traffic enforcement cameras (TECs) on the average transmission time. Moreover,...
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Rafał Leszczyna dr hab. inż.
OsobyDr hab. inż. Rafał Leszczyna jest profesorem uczelni na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej. W lipcu 2020 r., na podstawie osiągnięcia naukowego w obszarze zarządzania cyberbezpieczeństwem infrastruktur krytycznych w sektorze elektroenergetycznym, uzyskał stopień doktora habilitowanego w dziedzinie nauk inżynieryjno-technicznych, dyscyplina informatyka techniczna i telekomunikacja. W latach 2004–2008 pracował...
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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublikacjaIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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Dekodowanie kodów iterowanych z użyciem sieci neuronowej
PublikacjaNadmiarowe kody iterowane są jedną z prostych metod pozyskiwania długich kodów korekcyjnych zapewniających dużą ochronę przed błędami. Jednocześnie, chociaż ich podstawowy iteracyjny dekoder jest prosty koncepcyjnie oraz łatwy w implementacji, to nie jest on rozwiązaniem optymalnym. Poszukując alternatywnych rozwiązań zaproponowano, przedstawioną w pracy, strukturę dekodera tego typu kodów wspomaganą przez sieci neuronowe. Zaproponowane...
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublikacjaThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
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Indykatory mobilne GIS w analizie ruchu miejskiego
PublikacjaW ramach artykułu autorzy przedstawią możliwości monitorowania sytuacji komunikacyjnej miasta z wykorzystaniem autorskiego i dedykowanego systemu monitorowania ruchu w mieście, opartego o pakiet oprogramowania stacjonarnego i mobilnego przeznaczonego dla korporacji taxi. Celem publikacji jest przedstawienie założeń optymalnych i minimalnych do realizacji monitoringu ruchu w mieście. Przywołane zostaną autorskie próby wdrożeń rozwiązań...
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Potential and Use of the Googlenet Ann for the Purposes of Inland Water Ships Classification
PublikacjaThis article presents an analysis of the possibilities of using the pre-degraded GoogLeNet artificial neural network to classify inland vessels. Inland water authorities monitor the intensity of the vessels via CCTV. Such classification seems to be an improvement in their statutory tasks. The automatic classification of the inland vessels from video recording is a one of the main objectives of the Automatic Ship Recognition and...
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Segmentation Quality Refinement in Large-Scale Medical Image Dataset with Crowd-Sourced Annotations
PublikacjaDeployment of different techniques of deep learning including Convolutional Neural Networks (CNN) in image classification systems has accomplished outstanding results. However, the advantages and potential impact of such a system can be completely negated if it does not reach a target accuracy. To achieve high classification accuracy with low variance in medical image classification system, there is needed the large size of the...