Search results for: convolutional neural networks - Bridge of Knowledge

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Search results for: convolutional neural networks

  • A compact smart sensor based on a neural classifier for objects modeled by Beaunier's model

    A new solution of a smart microcontroller sensor based on a simple direct sensor-microcontroller interface for technical objects modeled by two-terminal networks and by the Beaunier’s model of anticorrosion coating is proposed. The tested object is stimulated by a square pulse and its time voltage response is sampled four times by the internal ADC of microcontroller. A neural classifier based on measurement data classifies the...

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  • An Analysis of Neural Word Representations for Wikipedia Articles Classification

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2019

    One of the current popular methods of generating word representations is an approach based on the analysis of large document collections with neural networks. It creates so-called word-embeddings that attempt to learn relationships between words and encode this information in the form of a low-dimensional vector. The goal of this paper is to examine the differences between the most popular embedding models and the typical bag-of-words...

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  • Resilient Routing in Communication Networks

    Publication

    - Year 2015

    This important text/reference addresses the latest issues in end-to-end resilient routing in communication networks. The work highlights the main causes of failures of network nodes and links, and presents an overview of resilient routing mechanisms, covering issues related to the Future Internet (FI), wireless mesh networks (WMNs), and vehicular ad-hoc networks (VANETs). For each of these network architectures, a selection of...

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  • Evolving neural network as a decision support system — Controller for a game of “2048” case study

    Publication

    The paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...

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  • Towards a classification of networks with asymmetric inputs

    Publication

    - NONLINEARITY - Year 2021

    Coupled cell systems associated with a coupled cell network are determined by (smooth) vector fields that are consistent with the network structure. Here, we follow the formalisms of Stewart et al (2003 SIAM J. Appl. Dyn. Syst. 2, 609–646), Golubitsky et al (2005 SIAM J. Appl. Dyn. Syst. 4, 78–100) and Field (2004 Dyn. Syst. 19, 217–243). It is known that two non-isomorphic n-cell coupled networks can determine the same sets of...

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  • Categorization of emotions in dog behavior based on the deep neural network

    The aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...

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  • The reliability of tree and star networks.

    Publication

    - Year 2008

    One of the important parameters characterizing the quality of computer networks is the network's reliability with respect to failures of the communication links and nodes. This chapter investigated the reliability of tree and star networks. The tree and star topology is used in centralized computer networks. In centralized computer networks all communication must take place through some central computer. Following measures of network...

  • Communication Networks in the Service of the Environmental Monitoring

    In the paper selected issues relating to communication networks in the services of the environmental monitoring (EM) have been described. It is divided into three main parts: introduction, wire and wireless networks. At the beginning of the basic definitions were explained. The wire part focuses on a plain old telephone service (POTS), an integrated services digital network (ISDN), a digital subscriber line (DSL) and a fiber-optic...

  • Evaluation of Facial Pulse Signals Using Deep Neural Net Models

    Publication

    - Year 2019

    The reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...

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  • Cost minimization in wireless networks with a bounded and unbounded number of interfaces

    Publication

    - NETWORKS - Year 2009

    Praca dotyczy problemu minimalizacji energii poprzez selektywne odłączanie urządzeń komunikacyjnych w wielointerfejsowych sieciach bezprzewodowych w taki sposób, by zapewnić realizację wymaganego grafu połączeń. Sformułowano problem optymalizacyjny, podano wyniki dotyczące jego trudności i zaproponowano algorytmy optymalizacyjne. Rozważono zarówno wariant, w którym liczba interfejsów komunikacyjnych jest parametrem stałym (narzuconym...

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  • Development of a tropical disease diagnosis system using artificial neural network and GIS

    Publication

    - Year 2021

    Expert systems for diagnosis of tropical diseases have been developed and implemented for over a decade with varying degrees of success. While the recent introduction of artificial neural networks has helped to improve the diagnosis accuracy of such systems, this aspect is still negatively affected by the number of supported diseases. A large number of supported diseases usually corresponds to a high number of overlapping symptoms,...

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  • New Two-center Ellipsoidal Basis Function Neural Network for Fault Diagnosis of Analog Electronic Circuits

    In the paper a new fault diagnosis-oriented neural network and a diagnostic method for localization of parametric faults in Analog Electronic Circuits (AECs) with tolerances is presented. The method belongs to the class of dictionary Simulation Before Test (SBT) methods. It utilizes dictionary fault signatures as a family of identification curves dispersed around nominal positions by component tolerances of the Circuit Under Test...

  • Adding Intelligence to Cars Using the Neural Knowledge DNA

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2017

    In this paper we propose a Neural Knowledge DNA based framework that is capable of learning from the car’s daily operation. The Neural Knowledge DNA is a novel knowledge representation and reasoning approach designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing devices. We examine our framework for drivers' classification based on their driving behaviour. The experimental...

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  • Overview of Scalability and Reliability Problem in SDN Networks

    In the paper an overview of scalability and reliability in the SDN (Software Defined Networks) networks has been presented. Problems and limitations for guaranteeing scalability and reliability in SDN networks have been indicated. Known methods for assuring scalability and reliability in SDN networks have been described. Projects from research communities for resolving issues with scalability and reliability in SDN networks have...

  • The reliability of tree and star networks

    This paper investigated the reliability of tree and star networks. Following measures of network reliability are assumed: the expected number of nodes, that can communicate with the central node; the expected number of node pairs, that are connected by a path through the central node; the expected number of node pairs communicating.

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  • Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors

    In the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...

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  • Neural Network-Based Sequential Global Sensitivity Analysis Algorithm

    Publication

    - Year 2022

    Performing global sensitivity analysis (GSA) can be challenging due to the combined effect of the high computational cost, but it is also essential for engineering decision making. To reduce this cost, surrogate modeling such as neural networks (NNs) are used to replace the expensive simulation model in the GSA process, which introduces the additional challenge of finding the minimum number of training data samples required to...

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  • Protection in elastic optical networks

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

    - IEEE NETWORK - Year 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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  • Toward Intelligent Recommendations Using the Neural Knowledge DNA

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2021

    In this paper we propose a novel recommendation approach using past news click data and the Neural Knowledge DNA (NK-DNA). The Neural Knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for news recommendation tasks on the MIND benchmark dataset. By taking advantages of NK-DNA, deep...

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  • THE UNSUSTAINABILITY OF PUBLIC-SECTOR ORGANIZATIONAL NETWORKS: A CASE STUDY OF VOLUNTARY COURT NETWORKS

    Publication

    - Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska - Year 2020

    Purpose: The purpose of this study is to identify the problem of sustainability of public-sector 12 organizational networks on the example of common courts and what it implies for further 13 research. Methodology: The study used qualitative research tools in the form of structured 14 interviews. Interviews were conducted with 36 presidents and directors of common courts. 15 After conducting and transcribing each interview, their...

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  • Exploiting Multi-Interface Networks: Connectivity and Cheapest Paths

    Publication

    - WIRELESS NETWORKS - Year 2009

    Rozważano zagadnienie minimalizacji energii w sieciach bezprzewodowych bez infrastruktury, w których niektóre węzły są wyposażone w więcej, niż jeden interfejs. W przyjętym modelu sieci podano nowe algorytmy przybliżone oraz wyniki dotyczące złożoności obliczeniowej dla dwóch problemów: aktywacji najtańszej spójnej podsieci spinającej oraz aktywacji ścieżki pomiędzy ustaloną parą węzłów.

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  • An efficient approach to optimization of semi‐stable routing in multicommodity flow networks

    Publication

    - NETWORKS - Year 2021

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  • A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks

    Publication

    The visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases...

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  • Rearrangeability in multicast Clos networks is NP-complete

    Publication

    Przestrajalność w polach Closa z połączeniami jeden do jeden jest problemem wielomianowym. W pracy pokazano, że w polach z połączeniami jeden do wiele problem ten jest NP zupełny.Three-stage elos networks are commutation networks with circuit switching. So far, graph theory has been very useful tool for solving issues related to these networks with unicast connections. This is so because if elos network is represented as a bipartite...

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  • Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements

    Publication

    - ENERGIES - Year 2022

    This article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...

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  • Controlling computer by lip gestures employing neural network

    Publication

    - Year 2010

    Results of experiments regarding lip gesture recognition with an artificial neural network are discussed. The neural network module forms the core element of a multimodal human-computer interface called LipMouse. This solution allows a user to work on a computer using lip movements and gestures. A user face is detected in a video stream from a standard web camera using a cascade of boosted classifiers working with Haar-like features....

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  • Cooperative Data Transmission in Wireless Vehicular Networks

    Publication

    - Year 2017

    The paper presents issues related to the cooperative transmission in wireless vehicular networks. Cooperative transmission involves the use of mobile terminals as relay stations to improve the transmission quality, improve network performance and reduce energy consumption. The paper presents the methods used to implement cooperative transmission and the types of cooperative networks.

  • DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES

    Malignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...

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  • Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks

    In this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...

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  • Optimization of Wireless Networks for Resilience to Adverse Weather Conditions

    Publication
    • M. Pióro
    • E. Fitzgerald
    • I. Kalesnikau
    • D. Nace
    • J. Rak

    - Year 2020

    In this chapter, we consider how adverse weather conditions such as rain or fog affect the performance of wireless networks, and how to optimize these networks so as to make them robust to these conditions. We first show how to analyze the weather conditions in order to make them useful for network optimization modelling. Using an example realistic network, we show how to optimize two types of wireless networks: free-space optical...

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  • Optical Sensor Based Gestures Inference Using Recurrent Neural Network in Mobile Conditions

    In this paper the implementation of recurrent neural network models for hand gesture recognition on edge devices was performed. The models were trained with 27 hand gestures recorded with the use of a linear optical sensor consisting of 8 photodiodes and 4 LEDs. Different models, trained off-line, were tested in terms of different network topologies (different number of neurons and layers) and different effective sampling frequency...

  • Topology recognition and leader election in colored networks

    Publication

    Topology recognition and leader election are fundamental tasks in distributed computing in networks. The first of them requires each node to find a labeled isomorphic copy of the network, while the result of the second one consists in a single node adopting the label 1 (leader), with all other nodes adopting the label 0 and learning a path to the leader. We consider both these problems in networks whose nodes are equipped with...

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  • CRVG - a new model for wireless networks topology generation

    Publication

    This paper presents a new model of wireless network topology generator. Its main advantage is the possibility of relatively sparse networks generation. Because no iteration is needed, the model can be used for massive generation of networks for testing. The topological properties of produced graphs place them in the class of scale free networks, resembling real ones.

  • The networking of the justice system as part of public court networks

    Publication

    - Year 2015

    The 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...

  • Statistical significance of displacements in heterogeneous control networks

    Publication

    - Geodesy and Cartography - Year 2013

    This paper proposes a modification of the classical process for evaluating the statistical significance of displacements in the case of heterogeneous (e.g. linear-angular) control networks established to deformation measurements and analysis. The basis for the proposed solution is the idea of local variance factors. The theoretical discussion was complemented with an example of its application on a simulated horizontal control...

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  • Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2018

    In this paper, we propose a novel intrusion detection approach using past driving experience and the neural knowledge DNA for in-vehicle information system security. The neural knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for classifying malicious vehicle control commands...

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  • Dataset Related Experimental Investigation of Chess Position Evaluation Using a Deep Neural Network

    Publication

    The idea of training Articial Neural Networks to evaluate chess positions has been widely explored in the last ten years. In this paper we investigated dataset impact on chess position evaluation. We created two datasets with over 1.6 million unique chess positions each. In one of those we also included randomly generated positions resulting from consideration of potentially unpredictable chess moves. Each position was evaluated...

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  • A Bayesian regularization-backpropagation neural network model for peeling computations

    Publication
    • S. Gouravaraju
    • J. Narayan
    • R. Sauer
    • S. S. Gautam

    - JOURNAL OF ADHESION - Year 2023

    A Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...

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  • Trust Management Method for Wireless Sensor Networks

    Publication

    - Year 2017

    A Wireless Sensor Network (WSN) is a network of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to cooperatively pass their data to the main location. The first wireless network that bore any real resemblance to a modern WSN is the Sound Surveillance System (SOSUS), developed by the United States Military in the 1950s to detect and track Soviet...

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  • Application of wavelength division multiplexing in sensor networks

    Publication

    - Year 2012

    Over the past few years the need to acquire data on various parameters from a number of sensors grew. The need that led to the development of a network of sensors which enables simultaneous control and measurement in a wide range of applications. The aim of this article is to discuss a possibility of connecting a variety of sensors in a network that would utilize WDM technology. Wavelength Division Multiplexing is commonly used...

  • Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm

    Publication

    A problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...

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  • Traffic Remapping Attacks in Ad Hoc Networks

    Publication

    - IEEE COMMUNICATIONS MAGAZINE - Year 2018

    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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  • Recurrent Neural Network Based Adaptive Variable-Order Fractional PID Controller for Small Modular Reactor Thermal Power Control

    This paper presents the synthesis of an adaptive PID type controller in which the variable-order fractional operators are used. Due to the implementation difficulties of fractional order operators, both with a fixed and variable order, on digital control platforms caused by the requirement of infinite memory resources, the fractional operators that are part of the discussed controller were approximated by recurrent neural networks...

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  • Intelligent turbogenerator controller based on artifical neural network

    The paper presents a desing of an intelligent controller based on neural network (ICNN). The ICNN ensures at the same time two fundamental functions : the maintaining of generator voltage at the desired value and the damping of the electromechanical oscillations. Its performance is evaluted on a single machine infinite bus power system through computer simulations. The dynamic and transient operation of the proposed controller...

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  • The impact of institutions on innovation networks: empirical evidence from Poland

    Publication

    - Technological and Economic Development of Economy - Year 2022

    Innovation networks may accelerate and improve the innovation process, while institutional pathologies may hamper it. This study employs the Kruskal-Wallis H test and regression analysis to determine if the relationship between institutions and innovation networks does exist among the investigated variables. The purpose of the study was to find out whether cooperation with special local institutions influences the innovative behaviour...

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  • Traffic Modeling in IMS-based NGN Networks

    In the modern world the need for accurate and quickly delivered information is becoming more and more essential. In order to fulfill these requirements, next generation telecommunication networks should be fast introduced and correctly dimensioned. For this reason proper traffic models must be identified, which is the subject of this paper. In the paper standardization of IMS (IP Multimedia Subsystem) concept and IMS-based NGN...

  • Interdependence between Power Grids and Communication Networks: A Resilience Perspective

    Publication
    • L. Martins
    • R. Girao-Silva
    • L. Jorge
    • A. Gomes
    • F. Musumeci
    • J. Rak

    - Year 2017

    Power network resilience is increasingly dependent on communication networks. Besides traditional generation, power networks need to accommodate increasingly high penetration levels of dispersed micro generation, mostly based on renewable sources, and increasing and challenging demand, such as electric vehicles. At the same time the deployment of enabling technologies throughout the power grid makes available new demand resources...

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  • A METHOD OF TRUST MANAGEMENT IN WIRELESS SENSOR NETWORKS

    The research problem considered in this paper is how to protect wireless sensor networks (WSN) against cyber-threats by applying trust management and how to strengthen network resilience to attacks targeting the trust management mechanism itself. A new method, called WSN Cooperative Trust Management Method (WCT2M), of distributed trust management in multi-layer wireless sensor networks is proposed and its performance is evaluated....

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  • Neural network model of ship magnetic signature for different measurement depths

    Publication

    This paper presents the development of a model of a corvette-type ship’s magnetic signature using an artificial neural network (ANN). The capabilities of ANNs to learn complex relationships between the vessel’s characteristics and the magnetic field at different depths are proposed as an alternative to a multi-dipole model. A training dataset, consisting of signatures prepared in finite element method (FEM) environment Simulia...

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  • Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach

    Publication

    In 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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