Wyniki wyszukiwania dla: vehicle detection, traffic monitoring system, background subtraction, convolutional neural network - MOST Wiedzy

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Wyniki wyszukiwania dla: vehicle detection, traffic monitoring system, background subtraction, convolutional neural network

Wyniki wyszukiwania dla: vehicle detection, traffic monitoring system, background subtraction, convolutional neural network

  • Bioterrorism — characteristics and possibilities of prevention

    In the paper bioterrorist threats have been presented. Historical background and possible methods of attacks have been described. The most dangerous pathogens and disease entities have been classified. Selected methods of detection and identification of biological weapon have been presented. The wireless system for threats monitoring — developed at Gdansk University of Technology — has been described.

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  • Comparative study of neural networks used in modeling and control of dynamic systems

    Publikacja

    In this paper, a diagonal recurrent neural network that contains two recurrent weights in the hidden layer is proposed for the designing of a synchronous generator control system. To demonstrate the superiority of the proposed neural network, a comparative study of performances, with two other neural network (1_DRNN) and the proposed second-order diagonal recurrent neural network (2_DRNN). Moreover, to confirm the superiority...

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  • Travel Time of Public Transport Vehicles Estimation

    Effective prediction of speed is central to advanced traveler information and transportation management systems. The speed of public transport vehicles is affected by many external factors including traffic volume, organization and infrastructure. The literature presents methods for estimating travel time on sections of a transport network and vehicle arrival at stops, often making use of the AVL (automatic vehicle location). The...

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  • Resource constrained neural network training

    Publikacja

    Modern applications of neural-network-based AI solutions tend to move from datacenter backends to low-power edge devices. Environmental, computational, and power constraints are inevitable consequences of such a shift. Limiting the bit count of neural network parameters proved to be a valid technique for speeding up and increasing efficiency of the inference process. Hence, it is understandable that a similar approach is gaining...

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  • Pose-Invariant Face Detection by Replacing Deep Neurons with Capsules for Thermal Imagery in Telemedicine

    Abstract— The aim of this work was to examine the potential of thermal imaging as a cost-effective tool for convenient, non- intrusive remote monitoring of elderly people in different possible head orientations, without imposing specific behavior on users, e.g. looking toward the camera. Illumination and pose invariant head tracking is important for many medical applications as it can provide information, e.g. about vital signs, sensory...

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  • Estimation of the Regenerative Braking Process Efficiency in Electric Vehicles

    Publikacja

    In electric and hybrid vehicles, it is possible to recover energy from the braking process and reuse it to drive the vehicle using the batteries installed on-board. In the conditions of city traffic, the energy dissipated in the braking process constitutes a very large share of the total resistance to vehicle motion. Efficient use of the energy from the braking process enables a significant reduction of fuel and electricity consumption...

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  • Grzegorz Szwoch dr hab. inż.

    Grzegorz Szwoch urodził się w 1972 roku w Gdańsku. W latach 1991-1996 studiował na wydziale Elektroniki Politechniki Gdańskiej. W roku 1996 ukończył studia w Zakładzie Inżynierii Dźwięku (obecnie Katedra Systemów Multimedialnych), broniąc pracę dyplomową pt. Modelowanie fizyczne wybranych instrumentów muzycznych. W tym samym roku dołączył do zespołu badawczego Katedry jako uczestnik Studium Doktoranckiego. Od stycznia 2001 roku...

  • Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms

    To this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...

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  • Towards bees detection on images: study of different color models for neural networks

    Publikacja

    This paper presents an approach to bee detection in videostreams using a neural network classifier. We describe the motivationfor our research and the methodology of data acquisition. The maincontribution to this work is a comparison of different color models usedas an input format for a feedforward convolutional architecture appliedto bee detection. The detection process has is based on a neural...

  • Ranking Speech Features for Their Usage in Singing Emotion Classification

    Publikacja

    This paper aims to retrieve speech descriptors that may be useful for the classification of emotions in singing. For this purpose, Mel Frequency Cepstral Coefficients (MFCC) and selected Low-Level MPEG 7 descriptors were calculated based on the RAVDESS dataset. The database contains recordings of emotional speech and singing of professional actors presenting six different emotions. Employing the algorithm of Feature Selection based...

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  • Towards Cancer Patients Classification Using Liquid Biopsy

    Liquid biopsy is a useful, minimally invasive diagnostic and monitoring tool for cancer disease. Yet, developing accurate methods, given the potentially large number of input features, and usually small datasets size remains very challenging. Recently, a novel feature parameterization based on the RNA-sequenced platelet data which uses the biological knowledge from the Kyoto Encyclopedia of Genes and Genomes, combined with a classifier...

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  • Visual Object Tracking System Employing Fixed and PTZ Cameras

    The paper presents a video monitoring system utilizing fixed and PTZ cameras for tracking of moving objects. First type of camera provides image for background modelling, being employed for foreground objects localization. Estimated objects locations are then utilised for steering of PTZ cameras when observing targeted objects with high close-ups. Objects are classified into several classes, then basic event detection is being...

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  • Estimation of Vehicle Energy Consumption at Intersections Using Microscopic Traffic Models

    Publikacja

    This paper addresses issues related to modeling energy consumption and emissions using microscopic traffic simulations. This paper develops a method in which a traffic model is used to calculate the energy needed to travel through selected types of intersections. This paper focuses on energy consumption and derived values of calculated energy, which can be, for example, carbon dioxide emissions. The authors present a review of...

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  • Hardware-Software Implementation of a Sensor Network for CityTraffic Monitoring Using the FPGA- and ASIC-Based Sensor Nodes

    Artykuł opisuje prototypową sieć sensorową do monitorowania ruchu pojazdów w mieście. Węzły sieci sensorowej, wyposażone w kamerę o niskiej rozdzielczości, obserwują ulice i wykrywają poruszające się obiekty. Detekcja obiektów jest realizowana w oparciu o własny algorytm segmentacji obrazów, wykorzystujący podwójne odejmowanie tła, wykrywanie krawędzi i cieni, działający na dedykowanym systemie mikroelektronicznym typu ''System...

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  • Potential for ITS/ICT Solutions in Urban Freight Management

    The article presents a study on applying ITS solutions in planning and management of urban freight transport in Gdynia. The traffic management system Tristar which is under implementation and its related systems show a potential to assist in development of freight transport measures. Recommendations for urban freight policy development supplementing Gdynia's Sustainable Urban Mobility Plan were used as a basis for identification...

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  • Mask Detection and Classification in Thermal Face Images

    Face masks are recommended to reduce the transmission of many viruses, especially SARS-CoV-2. Therefore, the automatic detection of whether there is a mask on the face, what type of mask is worn, and how it is worn is an important research topic. In this work, the use of thermal imaging was considered to analyze the possibility of detecting (localizing) a mask on the face, as well as to check whether it is possible to classify...

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  • INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH

    Publikacja

    The Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...

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  • Analysis of the regenerative braking process for the urban traffic conditions

    In a regular drive system, with an internal combustion engine, vehicle braking is connected with the unproductive dissipation of kinetic and potential energy accumulated in the mass of the vehicle into the environment. This energy can constitute up to 70% of the energy used to drive a vehicle under urban conditions. Its recovery and reuse is one of the basic advantages of hybrid and electric vehicles. Modern traffic management...

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  • Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition

    Publikacja

    - JOURNAL OF THE AUDIO ENGINEERING SOCIETY - Rok 2018

    convolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...

  • Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks

    Publikacja
    • T. Dziubich
    • P. Białas
    • Ł. Znaniecki
    • J. Halman
    • J. Brzeziński

    - Rok 2020

    One of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...

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  • The application of microscopic models in the study of pedestrian traffic

    Cities (especially in Central and Eastern Europe) focus on improving the road network, which aims to improve the efficiency of motor traffic and minimize congestion. Most of existing tools for analysing the effectiveness of urban transport networks do not assume to analyse the impact of walking and cycling on efficiency of transport systems. It is therefore necessary to develop solutions...

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  • Neural network training with limited precision and asymmetric exponent

    Publikacja

    Along with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...

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  • An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks

    Publikacja

    - Journal of Artificial Intelligence and Soft Computing Research - Rok 2023

    In this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...

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  • Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks

    Publikacja

    - IEEE Access - Rok 2022

    Object detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...

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  • Intelligent Autonomous Robot Supporting Small Pets in Domestic Environment

    In this contribution, we present preliminary results of the student project aimed at the development of an intelligent autonomous robot supporting small pets in a domestic environment. The main task of this robot is to protect a freely moving small pets against accidental stepping on them by home residents. For this purpose, we have developed the mobile robot which follows a pet and makes an alarm signal when a human is approaching....

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  • Detecting type of hearing loss with different AI classification methods: a performance review

    Publikacja
    • M. Kassjański
    • M. Kulawiak
    • T. Przewoźny
    • D. Tretiakow
    • J. Kuryłowicz
    • A. Molisz
    • K. Koźmiński
    • A. Kwaśniewska
    • P. Mierzwińska-Dolny
    • M. Grono

    - Rok 2023

    Hearing is one of the most crucial senses for all humans. It allows people to hear and connect with the environment, the people they can meet and the knowledge they need to live their lives to the fullest. Hearing loss can have a detrimental impact on a person's quality of life in a variety of ways, ranging from fewer educational and job opportunities due to impaired communication to social withdrawal in severe situations. Early...

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  • Sensorless Fault Detection of Induction Motor with Inverter Output Filter

    Publikacja

    The paper presents the problem of monitoring and fault detection of a sensorless voltage inverter fed squirrel cage induction motor with LC filter. The detection is based on load torque estimation of the investigated torque transmission system. The load torque is calculated besides the computation of other variables that are mandatory for sensorless drive operation such as rotor flux and speed. The implemented LC filter smooths...

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  • Performance improvement of NN based RTLS by customization of NN structure - heuristic approach

    Publikacja

    - Rok 2015

    The purpose of this research is to improve performance of the Hybrid Scene Analysis – Neural Network indoor localization algorithm applied in Real-time Locating System, RTLS. A properly customized structure of Neural Network and training algorithms for specific operating environment will enhance the system’s performance in terms of localization accuracy and precision. Due to nonlinearity and model complexity, a heuristic analysis...

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  • Deep Features Class Activation Map for Thermal Face Detection and Tracking

    Publikacja

    - Rok 2017

    Recently, capabilities of many computer vision tasks have significantly improved due to advances in Convolutional Neural Networks. In our research, we demonstrate that it can be also used for face detection from low resolution thermal images, acquired with a portable camera. The physical size of the camera used in our research allows for embedding it in a wearable device or indoor remote monitoring solution for elderly and disabled...

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  • Module of priorities for public transport vehicles in the TRISTAR system

    Publikacja

    One of the most important elements of the intelligent traffic control systems is the ability to control movement in such a way as to privilege the selected users movement, in particular public transport vehicles. Implemented at the Tri-City the TRISTAR system will also have a module for prioritizing public transport vehicles. The article presents a characteristics of the priority action system: the way of communication with the...

  • Resolving Conflicts in Object Tracking in Video Stream Employing Key Point Matching

    Publikacja

    - Rok 2012

    A novel approach to resolving ambiguous situations in object tracking in video streams is presented. The proposed method combines standard tracking technique employing Kalman filters with global feature matching method. Object detection is performed using a background subtraction algorithm, then Kalman filters are used for object tracking. At the same time, SURF key points are detected only in image sections identified as moving...

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  • Audio content analysis in the urban area telemonitoring system

    Publikacja

    Artykuł przedstawia możliwości rozwinięcie monitoringu miejskiego o automatyczną analizę dźwięku. Przedstawiono metody parametryzacji dźwięku, które możliwe są do zastosowania w takim systemie oraz omówiono aspekty techniczne implementacji. W kolejnej części przedstawiono system decyzyjny oparty na drzewach zastosowany w systemie. System ten rozpoznaje dźwięki niebezpieczne (strzał, rozbita szyba, krzyk) wśród dźwięków zarejestrowanych...

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  • Mobile indicators in GIS and GPS positioning accuracy in cities

    The publication describes the possible use of tele-geoprocessing as a synergy of modern IT solutions, telecommunications and GIS algorithms. The paper presents a possibility of urban traffic monitoring with the use of mobile GIS indicators of dedicated monitoring system designed for taxi corporation. The system is based on a stationary and mobile software package. The optimal and minimal assumptions for the monitoring of urban...

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  • Super-resolved Thermal Imagery for High-accuracy Facial Areas Detection and Analysis

    In this study, we evaluate various Convolutional Neural Networks based Super-Resolution (SR) models to improve facial areas detection in thermal images. In particular, we analyze the influence of selected spatiotemporal properties of thermal image sequences on detection accuracy. For this purpose, a thermal face database was acquired for 40 volunteers. Contrary to most of existing thermal databases of faces, we publish our dataset...

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  • Optimized Deep Learning Model for Flood Detection Using Satellite Images

    Publikacja
    • A. Stateczny
    • H. D. Praveena
    • R. H. Krishnappa
    • K. R. Chythanya
    • B. B. Babysarojam

    - Remote Sensing - Rok 2023

    The increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...

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  • Traffic Remapping Attacks in Ad Hoc Networks

    Publikacja

    Ad hoc networks rely on the mutual cooperation of stations. As such, they are susceptible to selfish attacks that abuse network mechanisms. Class-based QoS provisioning mechanisms, such as the EDCA function of IEEE 802.11, are particularly prone to traffic remapping attacks, which may bring an attacker better QoS without exposing it to easy detection. Such attacks have been studied in wireless LANs, whereas their impact in multihop...

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  • Protection in elastic optical networks

    Publikacja
    • R. Goścień
    • K. Walkowiak
    • M. Klinkowski
    • J. Rak

    - IEEE NETWORK - Rok 2015

    In this article, we analyze gains resulting from the use of EON architectures with special focus on transportation of cloud-ready and content-oriented traffic in the context of network resilience. EONs are a promising approach for future optical transport networks and, apart from improving the network spectral efficiency, bring such new capabilities as squeezed protection, which reduces resource requirements in failure scenarios....

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  • Automatic Incident Detection at Intersections with Use of Telematics

    While there are many examples of Intelligent Transport System deployments in Poland, more attention should be paid to traffic incident management and detection on dual-carriageways and urban street networks. One of the aims of CIVITAS DYN@MO, a European Union funded project, is to use TRISTAR (an Urban Transport Management System) detection modules to detect incidents at junctions equipped with traffic signals. First part of paper...

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  • Comparing the Effectiveness of ANNs and SVMs in Forecasting the Impact of Traffic-Induced Vibrations on Building

    Traffic - 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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  • Faults and Fault Detection Methods in Electric Drives

    Publikacja

    The chapter presents a review of faults and fault detection methods in electric drives. Typical faults are presented that arises for the induction motor, which is valued in the industry for its robust construction and cost-effective production. Moreover, a summary is presented of detectable faults in conjunction with the required physical information that allow a detection of specific faults. In order to address faults of a complete...

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  • Examining the Impact of Distance Between VSL Road Signs on Vehicle Speed Variance

    Publikacja

    - IEEE Access - Rok 2023

    Variable speed limit (VSL) is an intelligent transportation system (ITS) solution for traffic management. The speed limits can be changed dynamically to adapt to traffic conditions such as visibility and traffic volume, curvature, and grip coefficient of the road surface. The VSL traffic sign location problem and attempts to solve it using computer simulation are presented in this paper. Experiments on a selected road segment,...

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  • Moving object detection and tracking for the purpose of multimodal surveillance system in urban areas

    Publikacja

    - Rok 2008

    Background subtraction method based on mixture of Gaussians was employed to detect all regions in a video frame denoting moving objects. Kalman filters were used for establishing relations between the regions and real moving objects in a scene and for tracking them continuously. The objects were represented by rectangles. The objects coupling with adequate regions including the relation of many-to-many was studied experimentally...

  • TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK

    The need for precise detection of toxic gases drives development of new gas sensors structures and methods of processing the output signals from the sensors. In literature, artificial neural networks are considered as one of the most effective tool for the analysis of gas sensors or sensors arrays responses. In this paper a method of toxic gas components identification using a electrocatalytic gas sensor as a detector and an artificial...

  • Automatic road traffic safety management system in urban areas

    Publikacja

    Traffic incidents and accidents contribute to decreasing levels of transport system reliability and safety. Traffic management and emergency systems on the road, using, among others, automatic detection, video surveillance, communication technologies and institutional solutions improve the organization of the work of various departments involved in traffic and safety management. Automation of incident management helps to reduce...

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  • Self-Organizing Wireless Nodes Monitoring Network

    The concept of data monitoring system and self-organizing network of multipurpose data transfer nodes are presented. Two practical applications of this system are also presented. The first of these is the wireless monitoring system for containers, and the second is the mobile monitoring system for gas air pollution measurements.

  • Examining Impact of Speed Recommendation Algorithm Operating in Autonomous Road Signs on Minimum Distance between Vehicles

    Publikacja

    - Remote Sensing - Rok 2022

    An approach to a new kind of recommendation system design that suggests safe speed on the road is presented. Real data obtained on roads were used for the simulations. As part of a project related to autonomous road sign development, a number of measurements were carried out on both local roads and expressways. A speed recommendation model was created based on gathered traffic data employing the traffic simulator. Depending on...

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  • Leakage detection and localisation in drinking water distributionnetworks by MultiRegional PCA

    Publikacja

    Monitoring is one of the most important steps in advanced control of complex dynamic systems. Precise information about systems behaviour, including faults indicating, enables for efficient control. The paper describes an approach to detection and localisation of pipe leakage in Drinking Water Distribution Systems (DWDS) representing complex and distributed dynamic system of large scale. Proposed MultiRegional Principal Component...

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  • Equal Baseline Camera Array—Calibration, Testbed and Applications

    Publikacja

    - Applied Sciences-Basel - Rok 2021

    This paper presents research on 3D scanning by taking advantage of a camera array consisting of up to five adjacent cameras. Such an array makes it possible to make a disparity map with a higher precision than a stereo camera, however it preserves the advantages of a stereo camera such as a possibility to operate in wide range of distances and in highly illuminated areas. In an outdoor environment, the array is a competitive alternative...

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  • Wireless systems of threats monitoring

    The concept of wireless system of threats monitoring with self-organizing network of multipurpose data transfer nodes are presented. Two practical applications of this system are also presented. The first of these is the Global Wireless Monitoring System for Containers, and the second is the Mobile Monitoring System for Gas Air Pollution Measurements.

  • Wireless Systems of Threats Monitoring

    Concept of wireless system of threats monitoring with self-organizing network of multipurpose data transfer nodes are presented. Two practical applications of this system are also presented. The first of these is the Global Wireless Monitoring System for Containers and the second is the Mobile Monitoring System for Gas Air Pollution Measurements.