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Wyniki wyszukiwania dla: FIBER-REINFORCED CONCRETE BEAM, CHAINED MACHINE LEARNING MODEL, DUCTILITY INDEX, BENDING LOAD CAPACITY, ARTIFICIAL NEURAL NETWORKS
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Experimental and numerical investigations for GPR evaluation of reinforced concrete footbridge
PublikacjaThe GPR method has increasingly found application in non-destructive testing of reinforced concrete structures. This paper presents the new approach of modelling of the electromagnetic wave propagation for reinforced concrete structures with a complex system of the reinforcement. Simulations of the GPR field were performed on a three-dimensional model of a footbridge using the FDTD method. Numerical maps were compared with results...
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Electromagnetic Modeling of Microstrip Elements Aided with Artificial Neural Network
PublikacjaThe electromagnetic modeling principle aided withartificial neural network to designing the microwave widebandelements/networks prepared in microstrip technology is proposedin the paper. It is assumed that the complete information is knownfor the prototype design which is prepared on certain substratewith certain thickness and electric permittivity. The longitudinaland transversal dimensions of new design...
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Remote sensing and photogrammetry techniques in diagnostics of concrete structures
PublikacjaRecently laser scanning technologies become widely used in many areas of the modern economy. In the following paper authors show a potential spectrum of use Terrestrial Laser Scanning (TLS) in diagnostics of reinforced concrete elements. Based on modes of failure analysis of reinforcement concrete beam authors describe downsides and advantages of adaptation of terrestrial laser scanning to this purpose, moreover reveal under which...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublikacjaRenal 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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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublikacjaThis study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...
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Determination of Odour Interactions in Gaseous Mixtures Using Electronic Nose Methods with Artificial Neural Networks
PublikacjaThis paper presents application of an electronic nose prototype comprised of eight sensors, five TGS-type sensors, two electrochemical sensors and one PID-type sensor, to identify odour interaction phenomenon in two-, three-, four- and five-component odorous mixtures. Typical chemical compounds, such as toluene, acetone, triethylamine, α-pinene and n-butanol, present near municipal landfills and sewage treatment plants were subjected...
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Study on extraction and characterization of anchote (Coccinia abyssinica) starch and reinforced enset (Ensete ventricosum) fiber for the production of reinforced bioplastic film
PublikacjaPopulation expansion is causing an increase in dependence on plastic materials. The worst aspects of conventional plastics were their inability to biodegrade, their poor capacity to transmit water vapor, and their production of greenhouse gases. Usages of bioplastics are necessary for the advancement of a green economy and environment in order to eradicate these drawbacks of traditional plastics. In this study, reinforced bioplastic...
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Detection of debonding in reinforced concrete beams using ultrasonic transmission tomography and hybrid ray tracing technique
PublikacjaThis paper concerns inspection of reinforced concrete elements, with particular emphasis on assessing the quality of the adhesive connection between steel and concrete. A novel theoretical model was developed to determine the paths of transmitted, refracted and reflected elastic waves as well as a creeping wave propagated along the inclusion surface. Imaging the internal structure of tested beams was based on wave propagation measurements...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublikacjaIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Machine Learning and Electronic Noses for Medical Diagnostics
PublikacjaThe need for noninvasive, easy-to-use, and inexpensive methods for point-of-care diagnostics of a variety of ailments motivates researchers to develop methods for analyzing complex biological samples, in particular human breath, that could aid in screening and early diagnosis. There are hopes that electronic noses, that is, devices based on arrays of semiselective or nonselective chemical sensors, can fill this niche. Electronic...
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Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublikacjaOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...
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Application of Artificial Neural Networks in Investigations of Steam Turbine Cascades
PublikacjaZaprezentowano wyniki badań numerycznych zastosowania sieci neuronowych przy obliczeniach przepływów w palisadach turbin parowych. Na podstawie uzyskanych wyników wykazano, że sieci neuronowe mogą być używane do szacowania przestrzennego rozkładu parametrów przepływu, takich jak entalpia, entropia, ciśnienie czy prędkość czynnika w kanale przepływowym. Omówiono również zastosowania tego typu metod przy projektowaniu palisad, stopni...
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Prediction of antimicrobial activity of imidazole derivatives by artificial neural networks
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Forecasting of currency exchange rates using artificial neural networks
PublikacjaW rozdziale tym autor przedstawił wyniki swoich badań nad wykorzystaniem sztucznych sieci neuronowych do prognozowania kursu walut (na przykładzie pary walutowej PLN-USD).Głównym celem badań było porównanie skuteczności przewidywania kursu złotówki w latach 1997 - 2005 przy pomocy różnych rodzajów sieci neuronowych.
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Assessing the attractiveness of human face based on machine learning
PublikacjaThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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Exploring Neural Networks for Musical Instrument Identification in Polyphonic Audio
PublikacjaThe purpose of this paper is to introduce neural network-based methods that surpass state-of-the-art (SOTA) models, either by training faster or having simpler architecture, while maintaining comparable effectiveness in musical instrument identification in polyphonic music. Several approaches are presented, including two authors’ proposals, i.e., spiking neural networks (SNN) and a modular deep learning model named FMCNN (Fully...
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Ultrasound monitoring for evaluation of damage in reinforced concrete
PublikacjaThe paper deals with automated monitoring of damage evolution in concrete elements subjected to three-point bending tests. The monitoring is based on the nonlinear interactions of traveling ultrasonic waves with micro-crack zones inside the concrete specimens and surface-breaking cracks. The developed procedure assumes semi-continuous ultrasonic testing during the element full loading cycle and generation of the power spectral...
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Stability and load bearing capacity of a braced truss under upward wind loading
PublikacjaThe paper is focused on the numerical and experimental investigation of stability of a steel truss under upward wind loading. The structure was stiffened by elastic braces situated at the top and bottom chord. Usually the lateral (translational) brace stiffness is considered. However, the rotational stiffness of braces caused by interaction between torsional stiffness of the truss top chord and bending stiffness of the roof elements...
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Stability and load bearing capacity of a braced truss under upward wind loading
PublikacjaThe paper is focused on the numerical and experimental investigation of stability of a steel truss under upward wind loading. The structure was stiffened by elastic braces situated at the top and bottom chord. Usually the lateral (translational) brace stiffness is considered. However, the rotational stiffness of braces caused by interaction between torsional stiffness of the truss top chord and bending stiffness of the roof elements...
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Characterization of corrosion in reinforced concrete beams using destructive and non-destructive tests
PublikacjaThe paper presents both non-destructive and destructive experimental tests on steel-reinforced concrete beams subjected to electrochemical corrosion. To examine the condition and behavior of the specimens, destructive tests were carried out, i.e., a three-point bending together with a modulated ultrasonic wave test. In addition, a series of non-destructive experiments were conducted, such as the potential measurement method, low-frequency...
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Fiber optic microsphere with a ZnO thin film for potential application in a refractive index sensor – theoretical study
PublikacjaOptical fiber sensors of refractive index play an important role in analysis of biological and chemical samples. This work presents a theoretical investigation of spectral response of a fiber optic microsphere with a zinc oxide (ZnO) thin film deposited on the surface and evaluates the prospect of using such a structure for refractive index sensing. A microsphere is fabricated by an optical fiber tapering method on the base of...
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Evaluation of the resistance of steel–concrete adhesive connection in reinforced concrete beams using guided wave propagation
PublikacjaThe development of the nondestructive diagnostic methods is of significant importance in the last decades. A special attention is paid to diagnostics of reinforced concrete structures, which are very popular in the civil engineering field. A possible use of the guided waves in the estimation of the resistance of steel–concrete adhesive connection is studied in the following paper. The relationships relating adhesive connection...
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Reinforced concrete thin wall dome after eighty years of operation in maritime climate environment
PublikacjaThe paper presents a description of the construction elements of the Gdynia Seaport main hall dome. Firstly, it provides information about the technical condition of the dome’s structure. Secondly, it examines the strength analysis of the thin-walled reinforced concrete dome covering. Throughout the last 80 years the building has been exposed to an unfavourable marine climate. The analysis of the state of stress and deformations...
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TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK
PublikacjaThe 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...
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High load capacity spur gears with conchoidal path of contact
PublikacjaThe present study is devoted to investigation of spur gears with a conchoidal path of contact and a convex-convex contact between teeth. The load capacity and energy efficiency were evaluated using both theoretical and experimental approaches. The theoretical analysis showed that the conchoidal gear pairs are 5–21% stronger in terms of contact stress and have similar energy efficiency as compared to the involute gear pairs of the...
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The use of GFRP tubes as load-bearing jackets in concrete-composite columns
PublikacjaThe paper presents the fields of applications of polymer composites in building structures. The use of composite glass fibre tubes is discussed in more detail. The laboratory methods used to test the mechanical properties of these pipes are presented. An original research program is presented, including six concrete-filled glass fibre tubes. The cylinders and columns made in this way were tested for their axial load capacity. Conclusions...
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Application of gpr method in diagnostics of reinforced concrete structures
PublikacjaThis paper presents an application of the ground penetration method (GPR) for diagnostics of reinforced concrete structures. In situ measurements were conducted for three civil engineering structures: the ground floor structure, the abutment of the railway viaduct and the concrete well. The dual polarized ground penetrating radar with the antenna operating at a center frequency of 2 GHz was used for GPR surveys. Three different...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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SIGNIFICANT GUIDELINE FOR THE DAMAGE INDICES APPLIED TO REINFORCED CONCRETE STRUCTURES
PublikacjaIn this paper, based on a deep overview and literature study, the different formulas proposed for damage indices (DIs) applied to reinforced concrete structures under monotonic or cyclic loading are classified and presented. The DIs are applied to quantify the damages to structures, ranging from zero to one. Normally, they are applied to make a decision for repairing or demolition of the structures in the post-earthquake phases. Keywords:...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublikacjaRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Experimental study on ultrasonic monitoring of splitting failure in reinforced concrete
PublikacjaThis paper investigates inspection of reinforced concrete elements sensitive to the splitting failure. The behaviour of a reinforced concrete specimen subjected to a tensile stress is considered. The damage detection procedure is based on the ultrasonic wave propagation technique. The piezoelectric transducers are located on both ends of the specimen and the measurements are taken periodically during the incrementally increased...
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Deep Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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ANALYSIS OF THE LOAD-CARRYING CAPACITY OF A HYDRODYNAMIC WATER-LUBRICATED BEARING IN A HYDROELECTRIC POwER PLANT
PublikacjaThe paper presents an analysis of the load-carrying capacity of a historic hydrodynamic water-lubricated radial bearing of an unconventional segment design installed in the Braniewo Hydroelectric Power Plant. The aim of the calculations was to determine whether the bearing operates in the conditions of hydrodynamic or mixed lubrication, as well as to establish the optimal geometry of the axial grooves allowing for the highest load-carrying...
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Physics-guided neural networks (PGNNs) to solve differential equations for spatial analysis
PublikacjaNumerous examples of physically unjustified neural networks, despite satisfactory performance, generate contradictions with logic and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage involves extending...
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Direct shear stress vs strain relation for fiber reinforced composites
PublikacjaThe majority of fiber reinforced composites exhibit strong non-linear behavior in in-plane shear state. The effect is attributed to the micro-cracks appearing in the matrix and can be modeled on the micro and macro level. In this work the author proposes constitutive laws describing the non-linear in-plane shear response, which can be alternative for the relations commonly considered in the literature. The proposed equations are...
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Influence of stirrups in a concrete shell on strengthening reinforced concrete column
PublikacjaTwelve concrete columns, with a 150x150mm square section and three columns with a circular section (d=200mm), are tested to investigate the effect of strengthening by RC jacket. Based on a confined concrete model for axial static loading, an analytical methods, reported in the literature are proposed to predict the behavior of columns with RC jacket. The results support the conception that the effect of strengthening depends...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublikacjaDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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SIMULATIONS OF FRACTURE IN CONCRETE BEAMS UNDER BENDING USING A CONTINUUM AND DISCRETE APPROACH
PublikacjaThe paper describes two-dimensional meso-scale results of fracture in notched concrete beams under bending. Concrete was modelled as a random heterogeneous 4-phase material composed of aggregate particles, cement matrix, interfacial transitional zones and air voids. Within continuum mechanics, the simulations were carried out with the finite element method based on a isotropic damage constitutive model enhanced by a characteristic...
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Analysis of electrical patterns activity in artificial multi-stable neural networks
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Artificial Neural Networks for Prediction of Antibacterial Activity in Series of Imidazole Derivatives
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The concept of application of artificial neural networks for cultivation controlof cartilages in bioreactors.
PublikacjaNowym elementem niniejszej pracy jest omówienie problemów związanych z możliwością sterowania parametrami hydrodynamicznymi hodowanej w bioreaktorze chrząstki stawowej przy wykorzystaniu sztucznych sieci neuronowych. Przedstawiona została architektura strategii sterowania hodowlą tkanki z zastosowaniem tych sieci.
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Processing of musical data employing rough sets and artificial neural networks
PublikacjaArtykuł opisuje założenia systemu automatycznej identyfikacji muzyki i dźwięków muzycznych. Dokonano przeglądu standardu MPEG-7, ze szczególnym naciskiem na parametry opisowe dźwięku. Przedyskutowano problemy analizy danych audio, związane z zastosowaniami wykorzystującymi MPEG-7. W oparciu o eksperymenty przedstawiono efektywność deskryptorów niskiego poziomu w automatycznym rozpoznawaniu dźwięków instrumentów muzycznych. Przedyskutowano...
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Processing of musical data employing rough sets and artificial neural networks
PublikacjaArtykuł opisuje założenia systemu automatycznej identyfikacji muzyki i dźwięków muzycznych. Dokonano przeglądu standardu MPEG-7, ze szczególnym naciskiem na parametry opisowe dźwięku. Przedyskutowano problemy analizy danych audio, związane z zastosowaniami wykorzystującymi MPEG-7. W oparciu o eksperymenty przedstawiono efektywność deskryptorów niskiego poziomu w automatycznym rozpoznawaniu dźwięków instrumentów muzycznych. Przedyskutowano...
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The effect of external load on ultrasonic wave attenuation in steel bars under bending stresses
PublikacjaThe stress state in deformed solids has a significant impact on the attenuation of an ultrasonic wave propagating through the medium. Measuring a signal with certain attenuation characteristics can therefore provide useful diagnostic information about the stress state in the structure. In this work, basic principles behind a novel attenuation-based diagnostic framework are introduced. An experimental study on steel bars under three-point...
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Preparation and Characterization of Microsphere ZnO ALD Coating Dedicated for the Fiber-Optic Refractive Index Sensor
PublikacjaWe report the fabrication of a novel fiber-optic sensor device, based on the use of a microsphere conformally coated with a thin layer of zinc oxide (ZnO) by atomic layer deposition (ALD), and its use as a refractive index sensor. The microsphere was prepared on the tip of a single-mode optical fiber, on which a conformal ZnO thin film of 200 nm was deposited using an ALD process based on diethyl zinc (DEZ) and water at 100 °C....
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublikacjaLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Parameter estimation of a discrete model of a reinforced concrete slab
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublikacjaThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...