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Search results for: HISTOGRAM
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Histogram of Gradients with Cell Average Intensity for Human Detection
PublicationThe modification of the descriptor in human detector using Histogram of Oriented Gradients and support vector machine is presented. The proposed modification requires inserting the average cell intensitiesresulting with the increase of the length of the descriptor from 3780 to 4200 values, but it is easy to compute and instantly gives 14-26% of miss rate improvement at 10^-4 False Positives Per Window (FPPW). The modification...
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Histogram of Oriented Gradients with Cell Average Brightness for Human Detection
PublicationA modification of the descriptor in a human detector using Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) is presented. The proposed modification requires inserting the values of average cell brightness resulting in the increase of the descriptor length from 3780 to 3908 values, but it is easy to compute and instantly gives ≈ 25% improvement of the miss rate at 10‒4 False Positives Per Window (FPPW). The...
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Comparison of two approaches to potential of mean force calculations of hydrophobic association: particle insertion and weighted histogram analysis methods
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Box-spline histograms for multivariate density estimation
PublicationW pracy podano ujednoliconą konstrukcję estymatora pochodnych gęstości oraz stałych asymptotycznych dla tej gęstości. Posłużono się histogramami box-splinowymi. Skorzystano z twierdzeń asymptotycznych dla operatorów związanych z tymi estymatorami.
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Detekcja zakłóceń impulsowych w sygnałach fonicznych z wykorzystaniem wygładzonych lokalnych histogramów sygnału
PublicationStreszczenie: W artykule omówiono parametryczną metodę detekcji zakłóceń impulsowych sygnałów fonicznych opartą o analizę wygładzonych, ocen rozkładów prawdopodobieństwa (histogramów) błędów resztowych sygnału. We wstępie scharakteryzowano ideę detekcji próbek nadmiarowych z wykorzystaniem testów statystycznych. Następnie omówiono metodę aproksymacji histogramu przy użyciu rozkładu t-Studenta. Na koniec przedstawiono wyniki doświadczalne,...
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Analysis of IMS/NGN Call Processing Performance Using Phase-Type Distributions Based on Experimental Histograms
PublicationThe paper describes our further research done with the proposed analytical and simulation traffic models of the Next Generation Network (NGN), which is standardized for delivering multimedia services with strict quality and includes elements of the IP Multimedia Subsystem (IMS). The aim of our models of a single IMS/NGN domain is to evaluate two standardized call processing performance parameters, which appropriate values are very...
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Sensitivity analysis of simple random beam models by means of Monte Carlo Methods using Variance Reductions Techniques
PublicationA probabilistic sensitivity analysis of two nonlinear bar structures is presented. The analysis is carried out on the basis of the Monte Carlo method. The imperfections of the structures and the applied loads are adapted as random variables. Based on all of the generated input variables, an output response of the system is sought. Afterwards, a coefficient responsible for the structure failure is calculated and the limit state...
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Probabilistic sensitivity of limit states of structures. The Monte Carlo simulation
PublicationDesign sensitivity deals with the variation of structural response, implicitly dependent on the design variables of the problem. An attempt is made to implement probabilistic notation in engineering sensitivity analysis. The procedure to implement the sensitivity of a structural limit state to a given basic variable is described in the paper - its main idea, depicted by a flowchart and numerical examples of engineering analysis....
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MEAN SHIFT BASED SEGMENTATION FOR BLEEDING REGIONS IN ENDOSCOPIC VIDEOS
PublicationWith a set of 38 manually marked bleeding regions form endoscopic videos, the authors attempted to find an optimal image segmentation method for reproducing doctor’s markup. Mean shift segmentation combined with HSV histogram segmentation were used as a segmentation method, which was then optimized by tuning the parameters of the method using global optimization algorithm. A target function for measuring the quality of segmentation was...
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Probabilistyczna analiza stanów granicznych układów prętowych. Zastosowanie metody symulacyjnej Monte Carlo.
PublicationW pracy przedstawiono koncepcję wyzanczania rozkładu prawdopodobieństwa stanu granicznego układu prętowego w oparciu o metodę symulacyjną Monte Carlo. Mnożnik obciążenia granicznego wyznaczany jest w każdym kroku symulacyjnym, rezultatem procesu symulacyjnego jest histogram. Niezawodność,lub prawdopodobieństwo awarii układu są charakterystykami rozkładu prawdopodobieństwa stanu granicznego. Przykąłd zamieszczony w pracy uwzględnia...
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Computational complexity and length of recorded data for fluctuation enhanced sensing method in resistive gas sensors
PublicationThis paper considers complexity and accuracy of data processing for gas detection using resistance fluctuation data observed in resistance gas sensors. A few selected methods were considered (Principal Component Analysis – PCA, Support Vector Machine – SVM). Functions like power spectral density or histogram were used to create input data vector for these algorithms from the observed resistance fluctuations. The presented considerations...
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Comparison of image pre-processing methods in liver segmentation task
PublicationAutomatic liver segmentation of Computed Tomography (CT) images is becoming increasingly important. Although there are many publications in this field there is little explanation why certain pre-processing methods were utilised. This paper presents a comparison of the commonly used approach of Hounsfield Units (HU) windowing, histogram equalisation, and a combination of these methods to try to ascertain what are the differences...
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Time-frequency analysis of acoustic signals using concentrated spectrogram
PublicationThe paper presents improved method of time-frequency (TF) analysis of discrete-time signals. The method involves signal's local group delay (LGD) and channelized instantaneous frequency (CIF) to purposely redistribute all Short-time Fourier transform (STFT) lines. Additionally, the energy concentration index (ECI) and some histogram-like statistics are used to evaluate readability of estimated TF distributions of the energy. Recorded...
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Analysing By-Products Interaction as an Industry Resource of Circular Economy in Ukraine and the World
PublicationThe paper analyses existing and current scientific developments and literature sources, which show the advantages and disadvantages of many different influences of waste in Ukraine and other countries of Europe and the world. As a research result, stable connections have been established between the factors and criteria in assessing the by-product interaction as an industry resource. In our research, we used programs R.Studio and...
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The Use of Cluster Analysis to Evaluate the Impact of COVID-19 Pandemic on Daily Water Demand Patterns
PublicationProper determination of unitary water demand and diurnal distribution of water consumption (water consumption histogram) provides the basis for designing, dimensioning, and all analyses of water supply networks. It is important in the case of mathematical modelling of flows in the water supply network, particularly during the determination of nodal water demands in the context of Extended Period Simulation (EPS). Considering the...
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Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublicationLand Use and Land Cover (LULC) monitoring is crucial for global transformation, sustainable land control, urban planning, urban growth prediction, and the establishment of climate regulations for long-term development. Remote sensing images have become increasingly important in many environmental planning and land use surveys in recent times. LULC is evaluated in this research using the Sat 4, Sat 6, and Eurosat datasets. Various...
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Probabilistic sensitivity of limit states of structures : The Monte Carlo simulation
PublicationThe main issue of the paper is the probabilistic sensitivity of the limit states of structures with respect to selected input design variables. Attempt to the problem is done by the dedicated Monte Carlo simulation procedure. Basic design variables are random variables of given probability distributions, presented in the form of random numbers. Uni-parametrical increment of the dominant basic variable (basic variables) is done,...
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Processing of acoustical data in a multimodal bank operating room surveillance system
PublicationAn automatic surveillance system capable of detecting, classifying and localizing acoustic events in a bank operating room is presented. Algorithms for detection and classification of abnormal acoustic events, such as screams or gunshots are introduced. Two types of detectors are employed to detect impulsive sounds and vocal activity. A Support Vector Machine (SVM) classifier is used to discern between the different classes of...
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Audio-visual surveillance system for application in bank operating room
PublicationAn audio-visual surveillance system able to detect, classify and to localize acoustic events in a bank operating room is presented. Algorithms for detection and classification of abnormal acoustic events, such as screams or gunshots are introduced. Two types of detectors are employed to detect impulsive sounds and vocal activity. A Support Vector Machine (SVM) classifier is used to discern between the different classes of acoustic...
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Controlling computer by lip gestures employing neural network
PublicationResults 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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A method of RTS noise identification in noise signals of semiconductor devices in the time domain
PublicationIn the paper a new method of Random Telegraph Signal (RTS) noise identification is presented. The method is based on a standardized histogram of instantaneous noise values and processing by Gram-Charlier series. To find a device generating RTS noise by the presented method one should count the number of significant coefficients of the Gram-Charlier series. This would allow to recognize the type of noise. There is always one (first)...
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Adaptive Method for Modeling of Temporal Dependencies between Fields of Vision in Multi-Camera Surveillance Systems
PublicationA method of modeling the time of object transition between given pairs of cameras based on the Gaussian Mixture Model (GMM) is proposed in this article. Temporal dependencies modeling is a part of object re-identification based on the multi-camera experimental framework. The previously utilized Expectation-Maximization (EM) approach, requiring setting the number of mixtures arbitrarily as an input parameter, was extended with the...
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Methods of trend removal in electrochemical noise data – overview
PublicationIn this paper we shall review popular methods of trend removal from electrochemical noise time records. The basic principles of operation of the six most popular methods are explained. The proposed methods are: high - pass filtering, Moving Average Removal, polynomial detrending, wavelet detrending, Empirical Mode Decomposition and Variational Mode Decomposition. Estimation of trend removal quality...
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Analiza sygnału mowy w foniatrii
PublicationPraca zawiera opis algorytmów analizy sygnału mowy opracowanych do zastosowań medycznych. Mają one znaczenie wspomagające w diagnostyce schorzeń krtani, objawiających się jako np. chrypka, dwugłos oraz nieprawidłowa artykulacja tonu krtaniowego (głos drżący). Opisano algorytmy służące do ekstrakcji tonu krtaniowego (parametr F0 i jego przebieg zmienności w czasie) oraz do wygładzania widma (np. do estymacji parametrów formantowych...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Przykłady realizacji i interpretacji wyników sondażowych pomiarów terenowych w czynnych systemach wodociągowych
PublicationW pracy przedstawiono przebieg realizacji i rezultaty sondażowych pomiarów terenowych w trzech układach dystrybucji wody o zróżnicowanym przewymiarowaniu sieci wodociągowej. Pomiary przeprowadzono w dążeniu do identyfikacji właściwości (cech) strukturalnych i funkcjonalnych układów po wieloletniej ich eksploatacji. Ustalenia te determinują opracowanie programu realizacji pomiarów dla potrzeb tarowania komputerowego modelu przepływu...
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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublicationIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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An automatic system for identification of random telegraph signal (RTS) noise in noise signals
PublicationIn the paper the automatic and universal system for identification of Random Telegraph Signal (RTS) noise as a non-Gaussian component of the inherent noise signal of semiconductor devices is presented. The system for data acquisition and processing is described. Histograms of the instantaneous values of the noise signals are calculated as the basis for analysis of the noise signal to determine the number of local maxima of histograms...
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Imaging forms in passive sonars
PublicationReferat jest kontynuacją tematyki organizacji zobrazowań we współczesnych systemach hydrolokacyjnych przedstawionej w referacie zaproszonym na ubiegłorocznym OSA dla systemów aktywnych. Tym razem dotyczy organizacji zobrazowań w systemach pasywnych. W praktyce, prócz prostych systemów nasłuchu i rejestracji dźwięków podwodnych, używanych przez badaczy fauny wodnej czy oceanografów, systemy pasywne są wykorzystywane w marynarkach...
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Podstawy cyfrowego przetwarzania obrazów. Problemy współczesnej nauki. Teoria i zastosowania. Informatyka.
PublicationNiniejsza książka prezentuje podstawy cyfrowego przetwarzania obrazów. Składa się z siedmiu rozdziałów, w których omawia się operacje na pikselach obrazu, histogramy, progowanie obrazów, filtry liniowe i nieliniowe, metody szkieletyzacji, wybrane operacje morfologiczne, transformację Houga, wyznaczanie cech geometrycznych obrazu.
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Wyznaczanie wydatków węzłowych w KMP na podstawie zbiorów odczytów wodomierzowych
PublicationW opracowaniu przedstawiono autorską metodę obliczania wydatków węzłowych w KMP na podstawie wyników analizy zbioru odczytów wodomierzowych. W rezultacie analiz ustalono, że o dynamice poboru wody w układzie wodociągowym decyduje nieliczna grupa największych odbiorców, a zdecydowana większość stanowi mało zmienne tło. Zastosowana metodyka sprawdziła się w ośmiu czynnych systemach wodociągowych.
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Wpływ specyficznych właściwości czynnych systemów wodociągowych w Polsce na metodykę pomiarów terenowych i interpretacje ich wyników
PublicationW opracowaniu scharakteryzowano trzy następujące cechy: 1) przewymiarowanie sieci wodociągowej, 2) pozorną chropowatość przewodów z odłożonymi osadami, 3) pulsację ciśnienia w układzie wodociągowym. Następnie wskazano na utrudnienia jakie one powodują w przygotowaniu pomiarów, ich przeprowadzeniu, a niekiedy interpretacji uzyskanych wyników. W efekcie dowiedziono, że normalne warunki eksploatacji nie pozwalają na bezpośrednie pomiary...
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A Simplified Method of Trend Removal to Determine Noise Observed During a Supercapacitor’s Discharging
PublicationIn this paper, new method of trend removal is proposed. This is a simplified method based on Empirical Mode Decomposition (EMD). The method was applied for voltage time series observed during supercapacitor discharging process. It assured the determination of an additive noise component after subtracting the identified trend component. We analyzed voltage time series observed between the terminals of the supercapacitor when discharged...