Wyniki wyszukiwania dla: 5G NETWORK SLICING VIRTUALISATION MARITIME COMMUNICATION 5G ARCHITECTURE - MOST Wiedzy

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Wyniki wyszukiwania dla: 5G NETWORK SLICING VIRTUALISATION MARITIME COMMUNICATION 5G ARCHITECTURE

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Wyniki wyszukiwania dla: 5G NETWORK SLICING VIRTUALISATION MARITIME COMMUNICATION 5G ARCHITECTURE

  • BeesyBees: A mobile agent-based middleware for a reliable and secure execution of service-based workflow applications in BeesyCluster

    Integrating distributed services into workflows comes with its own set of challenges, including security, coordination, fault tolerance and optimisation of execution time. This paper presents an architecture and implementation - nicknamed BeesyBees - that allows distributed execution of workflow applications in BeesyCluster using agents. BeesyCluster is a middleware that allows users to access distributed resources as well as publish...

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  • Secure Quaternion Feistel Cipher for DICOM Images

    An improved and extended version of a quaternion-based lossless encryption technique for digital image and communication on medicine (DICOM) images is proposed. We highlight and address several security flaws present in the previous version of the algorithm originally proposed by Dzwonkowski et al. (2015). The newly proposed secure quater- nion Feistel cipher (S-QFC) algorithm...

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  • Design of an Autonomous IoT Node Powered by a Perovskite-Based Wave Energy Converter

    This paper presents the results of experimental research focused on wave energy harvesting and its conversion to power Internet of Things (IoT) devices. The harvesting and conversion process was performed using a wave energy converter (WEC) consisting of a lead zirconate titanate piezoelectric ceramic perovskite material and a prototype power electronic circuit. The designed WEC was considered as a power supply for an end node...

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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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  • Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing

    Developing signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....

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  • Bees Detection on Images: Study of Different Color Models for Neural Networks

    Publikacja

    This paper presents an approach to bee detection in video streams using a neural network classifier. We describe the motivation for our research and the methodology of data acquisition. The main contribution to this work is a comparison of different color models used as an input format for a feedforward convolutional architecture applied to bee detection. The detection process has is based on a neural binary classifier that classifies...

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  • Applying artificial neural networks for modelling ship speed and fuel consumption

    Publikacja

    This paper deals with modelling ship speed and fuel consumption using artificial neural network (ANN) techniques. These tools allowed us to develop ANN models that can be used for predicting both the fuel consumption and the travel time to the destination for commanded outputs (the ship driveline shaft speed and the propeller pitch) selected by the ship operator. In these cases, due to variable environmental conditions, making...

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  • Characterizing the Scalability of Graph Convolutional Networks on Intel® PIUMA

    Publikacja
    • M. J. Adiletta
    • J. J. Tithi
    • E. Farsarakis
    • G. Gerogiannis
    • R. Adolf
    • R. Benke
    • S. Kashyap
    • S. Hsia
    • K. Lakhotia
    • F. Petrini... i 2 innych

    - Rok 2023

    Large-scale Graph Convolutional Network (GCN) inference on traditional CPU/GPU systems is challenging due to a large memory footprint, sparse computational patterns, and irregular memory accesses with poor locality. Intel’s Programmable Integrated Unffied Memory Architecture (PIUMA) is designed to address these challenges for graph analytics. In this paper, a detailed characterization of GCNs is presented using the Open-Graph Benchmark...

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  • The reliability of tree and star networks.

    Publikacja

    - Rok 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...

  • Testing Situation Awareness Network for the Electrical Power Infrastructure

    The contemporary electrical power infrastructure is exposed to new types of threats. The cause of such threats is related to the large number of new vulnerabilities and architectural weaknesses introduced by the extensive use of Information and Communication Technologies (ICT) in such complex critical systems. The power grid interconnection with the Internet exposes the grid to new types of attacks, such as Advanced Persistent...

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  • Spectrum Sensing Based on Hybrid Spectrum Handoff in Cognitive Radio Networks

    Publikacja

    - ENTROPY - Rok 2023

    The rapid advancement of wireless communication combined with insufficient spectrum exploitation opens the door for the expansion of novel wireless services. Cognitive radio network (CRN) technology makes it possible to periodically access the open spectrum bands, which in turn improves the effectiveness of CRNs. Spectrum sensing (SS), which allows unauthorized users to locate open spectrum bands, plays a fundamental part in CRNs....

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  • Emotion Recognition from Physiological Channels Using Graph Neural Network

    In recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...

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  • Progress towards a unified approach to entanglement distribution

    Publikacja

    - PHYSICAL REVIEW A - Rok 2015

    Entanglement distribution is key to the success of secure communication schemes based on quantum mechanics, and there is a strong need for an ultimate architecture able to overcome the limitations of recent proposals such as those based on entanglement percolation or quantum repeaters. In this work we provide a broad theoretical background for the development of such technologies. In particular, we investigate the question of whether...

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  • Architektura przyszłości – przekraczanie granic poprzez interfejsy

    Publikacja

    - Rok 2014

    Architektura przyszłości rozpatrywana jest w kontekście rozwoju technologii cyfrowych, które umożliwiają nadawanie obiektom architektonicznym cech interfejsów. Przekraczanie granic dotyczy więc nadawania architekturze nowych funkcji - funkcjonalności zapożyczonych ze świata wirtualnego, emisji informacji oraz interakcji. W tym ujęciu „interfejs architektoniczny” stanowi płaszczyznę komunikacji pomiędzy obiektem architektonicznym...

  • Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models

    Deep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...

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  • Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment

    Atmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...

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  • Urban scene semantic segmentation using the U-Net model

    Publikacja

    - Rok 2023

    Vision-based semantic segmentation of complex urban street scenes is a very important function during autonomous driving (AD), which will become an important technology in industrialized countries in the near future. Today, advanced driver assistance systems (ADAS) improve traffic safety thanks to the application of solutions that enable detecting objects, recognising road signs, segmenting the road, etc. The basis for these functionalities...

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  • Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets

    Artificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...

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  • Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia

    Publikacja

    - Rok 2024

    W pracy doktorskiej podjęto problem realizacji algorytmów głębokiego uczenia w warunkach deficytu danych uczących. Głównym celem było opracowanie podejścia optymalizującego strukturę sieci neuronowej oraz zastosowanie uczeniu dwuetapowym, w celu uzyskania mniejszych struktur, zachowując przy tym dokładności. Proponowane rozwiązania poddano testom na zadaniu klasyfikacji znamion skórnych na znamiona złośliwe i łagodne. W pierwszym...

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  • Testy platformy SAN dla sektora elektroenergetycznego

    Współczesna infrastruktura elektroenergetyczna jest narażona na zagrożenia związane z dużą liczbą nowych luk i słabo- ści architektonicznych wynikających z szerszego wykorzystania technologii informacyjnych i komunikacyjnych (ang. Information and Communication Technologies – ICT). Połączenie infrastruktury elektroenergetycznej z Internetem naraża ją na nowe rodzaje ataków, takie jak ataki typu APT (ang. Advanced Persistent Threats)...

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  • Application of commercial microwave links (CMLs) attenuation for quantitative estimation of precipitation

    Publikacja
    • M. Pasierb
    • Z. Bałdysz
    • J. Szturc
    • G. Nykiel
    • A. Jurczyk
    • K. Ośródka
    • M. Figurski
    • M. Wojtczak
    • C. Wojtkowski

    - METEOROLOGICAL APPLICATIONS - Rok 2024

    Precipitation estimation models are typically sourced by rain gauges, weather radars and satellite observations. A relatively new technique of precipitation estimation relies on the network of Commercial Microwave Links (CMLs) employed for cellular communication networks: the rain-inducted attenuation in the links enables the precipitation estimation. In the paper, it is analysed to what extent the precipitation derived from CML...

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  • ESPAR Antenna-Based WSN Node With DoA Estimation Capability

    In this paper, we present a low-cost energy-efficient electronically steerable parasitic array radiator (ESPAR) antenna-based wireless sensor network (WSN) node designed for IEEE 802.15.4 standard that is capable of performing direction of arrival (DoA) estimation in real-life outdoor environments. To this end, we propose the WSN node architecture, design and realization that utilizes NXP JN5168 radio frequency (RF) wireless transceiver...

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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...

  • 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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  • Decision making process using deep learning

    Publikacja

    - Rok 2019

    Endüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...

  • Cooperative control in production and logistics

    Publikacja
    • L. Monostori
    • P. Valckenaers
    • A. Dolgui
    • H. Panetto
    • M. Brdyś
    • B. Csáji

    - ANNUAL REVIEWS IN CONTROL - Rok 2015

    Classical applications of control engineering and information and communication technology (ICT) in production and logistics are often done in a rigid, centralized and hierarchical way. These inflexible approaches are typically not able to cope with the complexities of the manufacturing environment, such as the instabilities, uncertainties and abrupt changes caused by internal and external disturbances, or a large number and variety...

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  • Remote Stateful Autoconfiguration for Mobile IPv6 Nodes with Server Side Duplicate Address Detection

    Publikacja

    During interdomain handover, IPv6 node requires new address at its new location. Once the L2 handover procedure is completed, mobile node (MN) starts its IPv6 configuration, using stateless (router advertisements) or stateful (DHCPv6 communication) mode. Once the address is obtained, its uniqueness has to be verified, using Duplicate Address Detection (DAD) procedure. Depending on the interface type, this procedure may easily take...

  • Quality Analysis of Audio-Video Transmission in an OFDM-Based Communication System

    Publikacja

    - Rok 2022

    Application of a reliable audio-video communication system, brings many advantages. With the spoken word we can exchange ideas, provide descriptive information, as well as aid to another person. With the availability of visual information one can monitor the surrounding, working environment, etc. As the amount of available bandwidth continues to shrink, researchers focus on novel types of transmission. Currently, orthogonal frequency...

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  • Projektowanie i eksploatacja dróg szynowych z wykorzystaniem mobilnych pomiarów satelitarnych

    Publikacja

    - Rok 2018

    Niniejsza monografia zawiera szczegółowy opis aktywnych sieci geodezyjnych GNSS oraz modelowania dokładności określania pozycji w pomiarach satelitarnych. Omówiono również opracowaną technikę mobilnych pomiarów satelitarnych toru kolejowego oraz aplikacje związane z jej zastosowaniem w projektowaniu i eksploatacji dróg szynowych. Autorzy zawarli w pracy wyniki swoich badań, wykonywanych na przestrzeni lat 2009–2015. Badania przeprowadzono...

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  • Towards an experience based collective computational intelligence for manufacturing

    Knowledge based support can play a vital role not only in the new fast emerging information and communication technology based industry, but also in traditional manufacturing. In this regard, several domain specific research endeavors have taken place in the past with limited success. Thus, there is a need to develop a flexible domain independent mechanism to capture, store, reuse, and share manufacturing knowledge. Consequently,...

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  • Ekonomiczne aspekty zastosowania techniki Mobilnych Pomiarów Satelitarnych przy regulacji osi toru

    Publikacja

    Od 2009 roku interdyscyplinarny zespół naukowy Politechniki Gdańskiej i Akademii Marynarki Wojennej (a obecnie Akademii Morskiej w Gdyni) rozwija technikę Mobilnych Pomiarów Satelitarnych toru kolejowego. Technika ta polega na objeździe trasy ciągnikiem szynowym z przyczepą (wagonem-platformą) lub wózkami, z zainstalowanymi na tych pojazdach odbiornikami sygnałów satelitarnych. Umożliwia ona precyzyjne określenie współrzędnych...

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  • Microfluidically Frequency-Reconfigurable Compact Self-Quadruplexing Tunable Antenna with High Isolation Based on Substrate Integrated Waveguide

    Publikacja

    - Scientific Reports - Rok 2024

    This communication presents a novel concept of microfluidically frequency-reconfigurable self-quadruplexing tunable antenna for quad-band applications. At the initial design stage, a substrate-integrated square cavity is divided into four unequal quarter-mode cavity resonators by inserting an X-shaped slot on the top surface of the cavity. Applying four 50-ohm microstrip feed-lines to these four quarter-mode cavity resonators enables...

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  • Analysis of the impact of socio-economic development on road safety based on the example of Baltic Sea Region countries

    Publikacja

    Baltic Sea Region (BSR) is a specific region of Europe, bringing together countries with different levels of socio-economic development. The main common point is territorial access to the Baltic Sea and the importance of maritime transport in the transportation of goods. The region consists of 9 countries, including Germany, Poland, Lithuania, Latvia, Estonia, Finland, Sweden, Denmark and Russia (more specifically, Kaliningrad...

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  • Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate

    Publikacja

    - IEEE Access - Rok 2021

    Fast replacement models (or surrogates) have been widely applied in the recent years to accelerate simulation-driven design procedures in microwave engineering. The fundamental reason is a considerable—and often prohibitive—CPU cost of massive full-wave electromagnetic (EM) analyses related to solving common tasks such as parametric optimization or uncertainty quantification. The most popular class of surrogates are data-driven...

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  • Development of an AI-based audiogram classification method for patient referral

    Publikacja

    - Rok 2022

    Hearing loss is one of the most significant sensory disabilities. It can have various negative effects on a person's quality of life, ranging from impeded school and academic performance to total social isolation in severe cases. It is therefore vital that early symptoms of hearing loss are diagnosed quickly and accurately. Audiology tests are commonly performed with the use of tonal audiometry, which measures a patient's hearing...

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  • Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis

    Publikacja

    Renal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...

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  • Reinforced Secure Gossiping Against DoS Attacks in Post-Disaster Scenarios

    Publikacja

    - IEEE Access - Rok 2020

    During and after a disaster, the perceived quality of communication networks often becomes remarkably degraded with an increased ratio of packet losses due to physical damages of the networking equipment, disturbance to the radio frequency signals, continuous reconfiguration of the routing tables, or sudden spikes of the network traffic, e.g., caused by the increased user activity in a post-disaster period. Several techniques have...

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  • OOA-modified Bi-LSTM network: An effective intrusion detection framework for IoT systems

    Publikacja
    • S. S. Narayana Chintapalli
    • S. Prakash Singh
    • J. Frnda
    • B. P. Divakarachar
    • V. L. Sarraju
    • P. Falkowski-Gilski

    - Heliyon - Rok 2024

    Currently, 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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  • Personal branding of artists and art-designers: necessity or desire?

    Publikacja

    Purpose Personal branding becomes a new in-demand skill for all professionals today. To be well-known helps to achieve success in the networked business environment. Personal relationships and a good reputation in the reality of network economy help young artists and art designers move up the career ladder. This paper aims to discuss a problem of artists who often find it difficult to define their artistic and self-distinction...

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  • Performance and Security Testing for Improving Quality of Distributed Applications Working in Public/Private Network Environments

    Publikacja

    - Rok 2010

    The goal of this dissertation is to create an integrated testing approach to distributed applications, combining both security and performance testing methodologies, allowing computer scientist to achieve appropriate balance between security and performance charakterstics from application requirements point of view. The constructed method: Multidimensional Approach to Quality Analysis (MA2QA) allows researcher to represent software...

  • Analysis of IPv6 handovers in IEEE 802.16 environment

    The second generation of WiMAX solutions, based on IEEE 802.16-2005 standard, offers limited mobility support. Unfortunately, after quickly changing the point of attachment on the WiMAX data link layer (DLL), very slow and inefficient IPv6 reconfiguration takes place. Delays introduced by automatic configuration (DHCPv6 and IPv6 protocols) and Mobile IPv6 can easily diminish or even render useless all benefits gained using the...

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  • Energy efficiency of electric multiple units in suburban operation

    Publikacja

    - Rok 2023

    This thesis presents approach to analysis of energy efficiency of a suburban rail network, using novel models developed on the Matlab/Simulink basis. Necessary features and requirements for such models were determined thru in-depth review of the source literature in all applicable fields: electrified transportation systems, electric multiple units construction, vehicle drivetrains and finally, existing simulation methods. Existing...

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  • Model-Based Adaptive Machine Learning Approach in Concrete Mix Design

    Publikacja

    Concrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...

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  • DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION

    Publikacja
    • M. Maj
    • J. Borkowski
    • J. Wasilewski
    • S. Hrynowiecka
    • A. Kastrau
    • M. Liksza
    • P. Jasik
    • M. Treder

    - Rok 2022

    Objective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...

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