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Search results for: LARGE SCALE CLASSIFIER
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Practical Approach to Large-Scale Electronic Structure Calculations in Electrolyte Solutions via Continuum-Embedded Linear-Scaling Density Functional Theory
PublicationWe present the implementation of a hybrid continuum-atomistic model for including the effects of a surrounding electrolyte in large-scale density functional theory (DFT) calculations within the Order-N Electronic Total Energy Package (ONETEP) linear-scaling DFT code, which allows the simulation of large complex systems such as electrochemical interfaces. The model represents the electrolyte ions as a scalar field and the solvent...
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Uncertainty quantification of modal parameter estimates obtained from subspace identification: An experimental validation on a laboratory test of a large-scale wind turbine blade
PublicationThe uncertainty afflicting modal parameter estimates stems from e.g., the finite data length, unknown, or partly measured inputs and the choice of the identification algorithm. Quantification of the related errors with the statistical Delta method is a recent tool, useful in many modern modal analysis applications e.g., damage diagnosis, reliability analysis, model calibration. In this paper, the Delta method-based uncertainty...
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Radiation-induced Changes in Levels of Selected Proteins in Peripheral Blood Serum of Breast Cancer Patients as a Potential Triage Biodosimeter for Large-scale Radiological Emergencies
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Large‐Scale Traveling Ionospheric Disturbances Over the European Sector During the Geomagnetic Storm on March 23–24, 2023: Energy Deposition in the Source Regions and the Propagation Characteristics
PublicationMultiple Large-Scale Traveling Ionospheric Disturbances (LSTIDs) are observed in the European sector in both day-time and night-time during the magnetic storm on March 23–24, 2023. The Total Electron Content (TEC) observation from a network of GNSS receivers shows the propagation of LSTIDs with amplitudes between around 0.5 and 1 TECU originating from auroral and polar cusp regions down to southern Europe (35°N) with velocities...
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Impact of Large-scale urban interventions on contemporary city centers. Gdansk case study. Wpływ przedsiewzięć urbanistycznych dużej skali na centra miast. Studium przypadku Gdańska
PublicationLarge scale urban interventions have become a common development practice in cotemporary cities, allowing achieving rapid changes in their urban structure. They can be analyzed taking into account various perspectives. Some of them include planning and development models, transformation of brownfields and other types of distressed urban areas, as well as consequences and results of their implementation in existing urban structures....
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Serce dzielnicy w stanie embrionalnego rozwoju - śrómieście reurbanizowanego wielkiego osiedla w polskim mieście metropolitalnym = Heart of the districts in embrional faze of development -city core structures for the large scale housing in Polish metropolitan city
PublicationW ostatnich 10 latach obserwowana jest intensyfikacja procesu uzupełniania zabudowy śródmieścia Gdańska. Jest to z jednej strony kontynuacja odbudowy historycznego centrum miasta, z drugiej zaś rewitalizacja dzielnic o przewadze zabudowy z początku wieku obejmująca śródmiejskie tereny powojskowe i poprzemysłowe m.in dawnej Stoczni Gdańskiej, koszaty we Wrzeszczu. Liczne komercyjne projekty prowadzą do istotnych dogęszczeń funcjami...
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[Chapter] 22. Application of physical modeling to study combustion process-es and flow patterns in large-scale boilers and furmaces. W: Optical me- thods and data processing in heat and fluid flow. Ed. C. Greated, J. Cos-grove, J.M. Buick. Bury St. Edmunds. London: Profess. Eng. Publ.**2002 s. 267-277, 4 rys. bibliogr. 6 poz. Zastosowanie modelowania fizycznego do badania procesów spalania pola prze- pływu w przemysłowych kotłach i piecach.
PublicationRozdział zawiera wyniki badań modelowania fizycznego dwuwymiarowego i trój-wymiarowego pola przepływu i procesów spalania w wybranych urządzeniachprzemysłowych.
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Two Stage SVM and kNN Text Documents Classifier
PublicationThe paper presents an approach to the large scale text documents classification problem in parallel environments. A two stage classifier is proposed, based on a combination of k-nearest neighbors and support vector machines classification methods. The details of the classifier and the parallelisation of classification, learning and prediction phases are described. The classifier makes use of our method named one-vs-near. It is...
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How Specific Can We Be with k-NN Classifier?
PublicationThis paper discusses the possibility of designing a two stage classifier for large-scale hierarchical and multilabel text classification task, that will be a compromise between two common approaches to this task. First of it is called big-bang, where there is only one classifier that aims to do all the job at once. Top-down approach is the second popular option, in which at each node of categories’ hierarchy, there is a flat classifier...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid 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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Automated Classifier Development Process for Recognizing Book Pages from Video Frames
PublicationOne of the latest developments made by publishing companies is introducing mixed and augmented reality to their printed media (e.g. to produce augmented books). An important computer vision problem that they are facing is classification of book pages from video frames. The problem is non-trivial, especially considering that typical training data is limited to only one digital original per book page, while the trained classifier...
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Identification of the Contamination Source Location in the Drinking Water Distribution System Based on the Neural Network Classifier
PublicationThe contamination ingression to the Water Distribution System (WDS) may have a major impact on the drinking water consumers health. In the case of the WDS contamination the data from the water quality sensors may be efficiently used for the appropriate disaster management. In this paper the methodology based on the Learning Vector Quantization (LVQ) neural network classifier for the identification of the contamination source location...
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A compact smart sensor based on a neural classifier for objects modeled by Beaunier's model
PublicationA 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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Identification of category associations using a multilabel classifier
PublicationDescription of the data using categories allows one to describe it on a higher abstraction level. In this way, we can operate on aggregated groups of the information, allowing one to see relationships that do not appear explicit when we analyze the individual objects separately. In this paper we present automatic identification of the associations between categories used for organization of the textual data. As experimental data...
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A method of self-testing of analog circuits based on fully differential op-amps with theTCBF classifier
PublicationA new approach of self-testing of analog circuits based on fully differential op-amps of mixed-signal systems controlled by microcontrollers is presented. It consists of a measurement procedure and a fault diagnosis procedure. We measure voltage samples of a time response of a tested circuit on a stimulation of a unit step function given at the common-mode reference voltage input of the op-amp. The fault detection and fault localization...
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Pupil detection supported by Haar feature based cascade classifier for two-photon vision examinations
PublicationThe aim of this paper is to present a novel method, called Adaptive Edge Detection (AED), of extraction of precise pupil edge coordinates from eye image characterized by reflections of external illuminators and laser beams. The method is used for monitoring of pupil size and position during psychophysical tests of two-photon vision performed by dedicated optical set-up. Two-photon vision is a new phenomenon of perception of short-pulsed...
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imPlatelet classifier: image‐converted RNA biomarker profiles enable blood‐based cancer diagnostics
PublicationLiquid biopsies offer a minimally invasive sample collection, outperforming traditional biopsies employed for cancer evaluation. The widely used material is blood, which is the source of tumor-educated platelets. Here, we developed the imPlatelet classifier, which converts RNA-sequenced platelet data into images in which each pixel corresponds to the expression level of a certain gene. Biological knowledge from the Kyoto Encyclopedia...
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Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition
PublicationThe article presents the problem of parameter value selection of the multiclass ``one against all'' approach of an AdaBoost algorithm in tasks of object recognition based on two-dimensional graphical images. AdaBoost classifier with Haar features is still used in mobile devices due to the processing speed in contrast to other methods like deep learning or SVM but its main drawback is the need to assembly the results of binary...
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Cathodic Protection System of the Spiral Classifier at the KGHM Polska Miedź S.A. Ore Concentration Plant—Case Study of Commissioning and Control of Operating Parameters
PublicationThe project involved designing, constructing and commissioning a cathodic protection system for a selected spiral classifier operating at the KGHM Polska Miedź S.A. Ore Concentration Plant (O/ZWR). The authors developed a concept and assumptions regarding the corrosion protection of a large industrial device using a cathodic protection system with an external power source. Pre-project studies included conducting a trial polarization...
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ReFlexeNN - the Wearable EMG Interface with Neural Network Based Gesture Classification
PublicationThe electromyographic activity of muscles was measured using a wireless biofeedback device. The aim of the study was to examine the possibility of creating an automatic muscle tension classifier. Several measurement series were conducted and the participant performed simple physical exercises - forcing the muscle to increase its activity accordingly to the selected scale. A small wireless device was attached to the electrodes placed...
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Analysis of the Possibility of Using New Types of Protective Coatings and Abrasion-Resistant Linings under the Operating Conditions of the Spiral Classifier at KGHM Polska Miedź S.A. Ore Concentration Plant
PublicationA study was carried out to select the appropriate coatings for corrosion protection of the spiral classifier working at KGHM Polska Miedź S.A. Ore Concentration Plant. The abrasion resistance of selected protective coatings and wear-resistant linings was investigated using a DT-523 rotary abrasion tester with Taber CS-10 rubber abrasive discs. The average weight loss of the coatings after a cycle of 2000 revolutions was determined....
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Improving css-KNN Classification Performance by Shifts in Training Data
PublicationThis paper presents a new approach to improve the performance of a css-k-NN classifier for categorization of text documents. The css-k-NN classifier (i.e., a threshold-based variation of a standard k-NN classifier we proposed in [1]) is a lazy-learning instance-based classifier. It does not have parameters associated with features and/or classes of objects, that would be optimized during off-line learning. In this paper we propose...
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Towards Cancer Patients Classification Using Liquid Biopsy
PublicationLiquid biopsy is a useful, minimally invasive diagnostic and monitoring tool for cancer disease. Yet, developing accurate methods, given the potentially large number of input features, and usually small datasets size remains very challenging. Recently, a novel feature parameterization based on the RNA-sequenced platelet data which uses the biological knowledge from the Kyoto Encyclopedia of Genes and Genomes, combined with a classifier...
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Dangerous sound event recognition using Support Vector Machine classifiers
PublicationA method of recognizing events connected to danger based on their acoustic representation through Support Vector Machine classification is presented. The method proposed is particularly useful in an automatic surveillance system. The set of 28 parameters used in the classifier consists of dedicated parameters and MPEG-7 features. Methods for parameter calculation are presented, as well as a design of SVM model used for classification....
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New Two-center Ellipsoidal Basis Function Neural Network for Fault Diagnosis of Analog Electronic Circuits
PublicationIn 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...
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Weighted Clustering for Bees Detection on Video Images
PublicationThis work describes a bee detection system to monitor bee colony conditions. The detection process on video images has been divided into 3 stages: determining the regions of interest (ROI) for a given frame, scanning the frame in ROI areas using the DNN-CNN classifier, in order to obtain a confidence of bee occurrence in each window in any position and any scale, and form one detection window from a cloud of windows provided by...
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The passive operating mode of the linear optical gesture sensor
PublicationThe study evaluates the influence of natural light conditions on the effectiveness of the linear optical gesture sensor, working in the presence of ambient light only (passive mode). The orientations of the device in reference to the light source were modified in order to verify the sensitivity of the sensor. A criterion for the differentiation between two states - "possible gesture" and "no gesture" - was proposed. Additionally,...
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Improving automatic surveillance by sound analysis
PublicationAn automatic surveillance system, based on event detection in the video image can be improved by implementing algorithms for audio analysis. Dangerous or illegal actions are often connected with distinctive sound events like screams or sudden bursts of energy. A method for detection and classification of alarming sound events is presented. Detection is based on the observation of sudden changes in sound level in distinctive sub-bands...
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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublicationAccording to the European Society of Cardiology, globally the number of patients with heart failure nearly doubled from 33.5 million in 1990 to 64.3 million in 2017, and is further projected to increase dramatically in this decade, still remaining a leading cause of morbidity and mortality. One of the most frequently applied heart failure classification systems that physicians use is the New York Heart Association (NYHA) Functional...
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Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing
PublicationDeveloping 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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Evaluation of sound event detection, classification and localization in the presence of background noise for acoustic surveillance of hazardous situations
PublicationAn evaluation of the sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for separating foreground events from the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the classifier...
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Increasing efficiency of technological process by limiting impact of corrosive environment on operation of spiral classifiers
PublicationMost of the technological operations related to the preparation of the output to be enriched and to the production of the final copper concentrate take place with the use of water environment. Water management, besides using innovative technical and technological solutions, is a significant factor in the whole copper ore enrichment process. Mine water resources and surface water of the tailing pond named "Żelazny Most" are the...
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Examining Feature Vector for Phoneme Recognition
PublicationThe aim of this paper is to analyze usability of descriptors coming from music information retrieval to the phoneme analysis. The case study presented consists in several steps. First, a short overview of parameters utilized in speech analysis is given. Then, a set of time and frequency domain-based parameters is selected and discussed in the context of stop consonant acoustical characteristics. A toolbox created for this purpose...
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Mural i jego rola w przestrzeni zurbanizowanej
PublicationCzym tak naprawdę jest mural? Definicji jest bardzo wiele. Według Słownika języka polskiego PWN mural to „wielkie malowidło wykonane bezpośrednio na ścianie budynku”. Pierwotnymi malowidłami tego typu były prace naskalne z epoki paleolitu. Następnie ważnymi epokami dla rozwoju tego typu prac był starożytny Egipt i starożytny Rzym. Samo słowo „mural” pochodzi z języka hiszpańskiego (h. mural – ścienny; malarstwo ścienne). To dzięki...
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Problemy planowania rozwoju systemu transportowego w obszarach metropolitalnych – przykład Obszaru Metropolitalnego G-G-S
PublicationProblemy rozwoju systemów transportowych w metropoliach wynikają ze specyfiki tych obszarów, ich skali i struktury przestrzennej. Obszary te charakteryzują się dużą wewnętrzną integracją funkcjonalną oraz dobrze rozwiniętą siecią transportową. Dynamicznie rozwijające się obszary metropolitalne mają odrębne systemy zarządzania finansami, rozwią- zania prawne oraz administrację, a także własne organy planowania i zarządzania, które...
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Detection, classification and localization of acoustic events in the presence of background noise for acoustic surveillance of hazardous situations
PublicationEvaluation of sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for discerning between the events being in focus and the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the...
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MOST PODWIESZONY kreowanie przestrzeni i konsekwencje konstrukcyjne
PublicationProjektowanie i budowa - wyzwania dla projektantów i wykonawców mostów. Mosty podwieszone i wiszące ich estetyka i konsekwencje strukturalne. Artykuł dotyczy aspektów estetycznych i konstrukcyjnych zaprojektowanych pylonów dla mostów podwieszonych lub wiszących. Autor zwraca uwagę na fakt, że niezwykłe rozwiązanie konstrukcyjne zastosowane do kładki lub małego wiaduktu może działać prawidłowo dzięki zjawiskom efektu skali. Nadzwyczajne...
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Direct brain stimulation modulates encoding states and memory performance in humans
PublicationPeople often forget information because they fail to effectively encode it. Here, we test the hypothesis that targeted electrical stimulation can modulate neural encoding states and subsequent memory outcomes. Using recordings from neurosurgical epilepsy patients with intracranially implanted electrodes, we trained multivariate classifiers to discriminate spectral activity during learning that predicted remembering from forgetting,...
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Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
PublicationBackground: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant)...
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublicationThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
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Bees Detection on Images: Study of Different Color Models for Neural Networks
PublicationThis 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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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublicationIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....
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TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK
PublicationThe 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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Rough Set-Based Classification of EEG Signals Related to Real and Imagery Motion
PublicationA rough set-based approach to classification of EEG signals registered while subjects were performing real and imagery motions is presented in the paper. The appropriate subset of EEG channels is selected, the recordings are segmented, and features are extracted, based on time-frequency decomposition of the signal. Rough set classifier is trained in several scenarios, comparing accuracy of classification for real and imagery motion....
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Noise profiling for speech enhancement employing machine learning models
PublicationThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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Problemy mieszkaniowe w budującej się Gdyni, „mieście poszukiwaczy złota”
PublicationMiasto Gdynia, zbudowane zupełnie od podstaw w przeciągu kilkunastu lat, na przestrzeni lat 1923-1939, stanowiło jedno z najważniejszych przedsięwzięć inwestycyjnych II Rzeczypospolitej. Szybka budowa dwóch składowych tego nowoczesnego ośrodka, jakimi były port i miasto, wiązała się nierzadko z nowymi, wcześniej trudnymi do przewidzenia wyzwaniami natury planistycznej i organizacyjnej. W początkowych latach budowy Gdyni zapewnienie...
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Basic Hand Gestures Classification Based on Surface Electromyography
PublicationThis paper presents an innovative classification system for hand gestures using 2-channel surface electromyography analysis. The system developed uses the Support Vector Machine classifier, for which the kernel function and parameter optimisation are conducted additionally by the Cuckoo Search swarm algorithm. The system developed is compared with standard Support Vector Machine classifiers with various kernel functions. The average...
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Usage of Two-Center Basis Function Neural Classifiers in Compact Smart Resistive Sensors
PublicationA new solution of the smart resistance sensorwith the Two-Center Basis Function (TCBF) neuralclassifier, for which the resistance sensor is a component ofan anti-aliasing filter of an ADC is proposed. Thetemperature measurement procedure is based on excitationof the filter by square impulses, sampling time response ofthe filter and processing measured voltage values by theTCBF classifier. All steps of the measurement procedure...
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FEEDB: A multimodal database of facial expressions and emotions
PublicationIn this paper a first version of a multimodal FEEDB database of facial expressions and emotions is presented. The database contains labeled RGB-D recordings of people expressing a specific set of expressions that have been recorded using Microsoft Kinect sensor. Such a database can be used for classifier training and testing in face recognition as well as in recognition of facial expressions and human emotions. Also initial experiences...
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Voice command recognition using hybrid genetic algorithm
PublicationAbstract: Speech recognition is a process of converting the acoustic signal into a set of words, whereas voice command recognition consists in the correct identification of voice commands, usually single words. Voice command recognition systems are widely used in the military, control systems, electronic devices, such as cellular phones, or by people with disabilities (e.g., for controlling a wheelchair or operating a computer...