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Wyniki wyszukiwania dla: Machine learning
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Separation and determination of the group-type composition of modern base and lubricating oils with a wide range of polarity, especially emitted to the environment
PublikacjaLubricating oils are composed of base oils (>85% v/v) and enriching additives (<15% v/v). Three types of base oils may be distinguished: 1) traditional bases (obtained by low-volatile fractions from crude oil distillation refining), 2) synthetic bases (mainly poly-alpha-olefins, sometimes esters, especially succinic acid esters), 3) bases of natural origin (especially obtained from refined plant oils). The bases of natural origin...
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Effect of lag screw on stability of first metatarsophalangeal joint arthrodesis with medial plate
PublikacjaBackground: First metatarsophalangeal joint (MTP-1) arthrodesis is a commonly performed procedure in the treatment of disorders of the great toe. Since the incidence of revision after MTP-1 joint arthrodesis is not insignificant, a medial approach with a medially positioned locking plate has been proposed as a new technique. The aim of the study was to investigate the effect of the application of a lag screw on the stability and...
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Art and Healthcare - Healing Potential of Artistic Interventions in Medical Settings
PublikacjaThe stereotype of a machine for healing seems to be well rooted in common thinking and social perception of hospital buildings. The technological aspect of healthcare architecture has been influenced for several years by three major factors. The first is linked to the necessity of providing safety and security in the environment of elevated epidemiological risk. The second concerns the need for incorporating advanced technology...
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Investigations on fracture in reinforced concrete beams in 3-point bending using continuous micro-CT scanning
PublikacjaThis study explores a fracture process in rectangular reinforced concrete (RC) beams subjected to quasi-static three-point bending. RC beams were short and long with included longitudinal reinforcement in the form of a steel or basalt bar. The ratio of the shear span to the effective depth was 1.5 and 0.75. The focus was on the load–deflection diagram and crack formation. Three-dimensional (3D) analyses of the size and distribution...
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Modelling and analysis of a synchronous generator in more electric aircraft power system using Synopsys/Saber simulator = Modelowanie i analiza generatora synchronicznego w systemie elektroenergetycznym nowoczesnego samolotu. Zastosowanie symulatora Synopsys/Saber
PublikacjaStreszczenie angielskie: A model for studying synchronous machine (SM) dynamic behaviour in more electric aircraft (MEA) power system is developed and implemented in the Synopys/Saber simulation environment. The modelling language MAST has been used to elaborate the SM model. The elaborated model exhibit a network with the same number of external terminals/ports as the real SM, and represents its behaviour in terms of the electrical...
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Mechanical response of human thoracic spine ligaments under quasi-static loading: An experimental study
PublikacjaPurpose This study aimed to investigate the geometrical and mechanical properties of human thoracic spine ligaments subjected to uniaxial quasi-static tensile test. Methods Four human thoracic spines, obtained through a body donation program, were utilized for the study. The anterior longitudinal ligament (ALL), posterior longitudinal ligament (PLL), capsular ligament (CL), ligamenta flava (LF), and the interspinous ligament and...
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublikacjaThe 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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Piotr Szczuko dr hab. inż.
OsobyDr hab. inż. Piotr Szczuko w 2002 roku ukończył studia na Wydziale Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej zdobywając tytuł magistra inżyniera. Tematem pracy dyplomowej było badanie zjawisk jednoczesnej percepcji obrazu cyfrowego i dźwięku dookólnego. W roku 2008 obronił rozprawę doktorską zatytułowaną "Zastosowanie reguł rozmytych w komputerowej animacji postaci", za którą otrzymał nagrodę Prezesa Rady...
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General concept of functional safety - standarisation and sector aspects
PublikacjaRozdział poświęcono koncepcji bezpieczeństwa funkcjonalnego. Bezpieczeństwo funkcjonalne jest częścią bezpieczeństwa całkowitego zależną od odpowiedniej odpowiedzi systemów sterowania i/lub zabezpieczeń na sygnały wejściowe podczas wystąpienia stanów nienormalnych maszyny, instalacji lub obiektu podwyższonego ryzyka. Koncepcja bezpieczeństwa funkcjonalnego przedstawiona w normie IEC 51508 stanowi przykład dobrej praktyki inżynierskiej...
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Managing safety of industrial hazardous installations with emphasis on the control systems, interfaces and human factors
PublikacjaIn the paper a procedure for the layer of protection analysis (LOPA) as a tool to evaluate the risk of accident scenarios occurrence in hazardous installations is outlined. In such installations several protection layers exist. Human operator performance in each layer is unavoidable, but the role and tasks are different and depend on the context of situation. Based on suggestions form literature (EEMUA, CREAM) and own proposals...
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Medium-Voltage Drives: Challenges and existing technology
PublikacjaThe article presents an overview of state-of-art solutions, advances, and design and research trends in medium-voltage (MV) drive technologies - and also discusses the challenges and requirements associated with the use of such drives. The choice and deployment of MV drives in industries are associated with numerous requirements related to the front-end converter (grid side) and inverter (machine side). The focus is on solutions...
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Design advantages and analysis of a novel five-phase doubly-fed induction generator
PublikacjaPurpose – The purpose of this paper is to provide an analysis of the performance of a new five-phase doubly fed induction generator (DFIG). Design/methodology/approach – This paper presents the results of a research work related to fivephase DFIG framing, including the development of an analytical model, FEM analysis as well as the results of laboratory tests of the prototype. The proposed behavioral level analytical model is based...
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Cerclage cable augmentation does not increase stability of the fixation of intertrochanteric fractures. A biomechanical study
PublikacjaBackground: Intertrochanteric fractures with a posteromedial intermediate fragment are unstable because of the loss of medial support. Additional fixation with a cerclage is used in subtrochanteric fractures, but not in intertrochanteric fractures. The aim of this biomechanical study is to evaluate whether cerclage fixation improves stability of intertrochanteric fractures. Hypothesis: Our hypothesis is that the cerclage fixation...
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Conception and design of a hybrid exciter for brushless synchronous generator. Application for autonomous electrical power systems = Koncepcja i projekt hybrydowej wzbudnicy bezszczotkowego generatora synchronicznego. Zastosowanie w autonomicznych systemach elektroenergetycznych
PublikacjaIn this paper a hybrid excitation system for a brushless synchronous generator working with variable speed in an autonomous energy generation system (e.g. airplane power grid) has been presented. A conception of a dual-stator hybrid exciter has been proposed. Comparison study of classical and hybrid exciter has been carried out. For the electromagnetic calculation two approaches have been applied: an analytical approach (based...
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Performance of a new commercial high-definition 3D patient specific quality assurance system for CyberKnife robotic radiotherapy and radiosurgery
PublikacjaConventional two dimensional and low-definition measurement techniques for dosimetric verification of radiotherapy treatment deliveries are no longer adequate in the era of hypofractionation and extremely high dose gradients. New quality assurance (QA) tools with 3D capability and high definition are urgently needed. The purpose of this study was to evaluate the performance of one of the first such commercial systems as applied...
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The cement-bone bond is weaker than cement-cement bond in cement-in-cement revision arthroplasty. A comparative biomechanical study
PublikacjaThis study compares the strength of the native bone-cement bond and the old-new cement bond under cyclic loading, using third generation cementing technique, rasping and contamination of the surface of the old cement with biological tissue. The possible advantages of additional drilling of the cement surface is also taken into account. Femoral heads from 21 patients who underwent a total hip arthroplasty performed for hip arthritis...
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Jacek Rumiński prof. dr hab. inż.
OsobyWykształcenie i kariera zawodowa 2022 2016 2002 1995 1991-1995 Tytuł profesora Habilitacja Doktor nauk technicznych Magister inżynier Prezydent RP, dziedzina nauk inżynieryjno-technicznych, dyscyplina: inzyniera biomedyczna Politechnika Gdańska, Biocybernetyka i inżyniera biomedyczna, tematyka: „Metody wyodrębniania sygnałów i parametrów z różnomodalnych sekwencji obrazów dla potrzeb diagnostyki i wspomagania...
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Analysis of a micro electro-mechanical platform for laparoscopic surgery
PublikacjaNiniejsza praca ma na celu określenie możliwości zastosowania odkształcalnych urządzeń o kinematyce równoległej w mikro robotycznych przegubach dla igło-laparoskopii. Operacje chirurgiczne przeprowadzane z użyciem narzędzi laparoskopowych o zmniejszonej średnicy nazywane są igłoskopią (z ang. needlescopy). Narzędzia te pozwalają na przeprowadzanie precyzyjnych operacji na stosunkowo niewielkim obszarze i z zaletami mało inwazyjnych...
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Paweł Nadachowski mgr inż.
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Karol Baran
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Adam Brzeski dr inż.
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Konrad Stawiski dr n. med.
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Labeler-hot Detection of EEG Epileptic Transients
PublikacjaPreventing early progression of epilepsy and sothe severity of seizures requires effective diagnosis. Epileptictransients indicate the ability to develop seizures but humansoverlook such brief events in an electroencephalogram (EEG)what compromises patient treatment. Traditionally, trainingof the EEG event detection algorithms has relied on groundtruth labels, obtained from the consensus...
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Artificial intelligence models in prediction of response to cardiac resynchronization therapy: a systematic review
PublikacjaThe aim of the presented review is to summarize the literature data on the accuracy and clinical applicability of artificial intelligence (AI) models as a valuable alternative to the current guidelines in predicting cardiac resynchronization therapy (CRT) response and phenotyping of patients eligible for CRT implantation. This systematic review was performed...
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Application of Artificial Intelligence by Poland’s Public Administration
PublikacjaThis chapter presents an overview and analysis of artificial intelligence-driven solutions created and implemented by or with the support of Poland’s central public administration (PA). After discussing governance of AI-related issues, we analyze a set of examples of AI innovation to map the actors and their relations within the ecosystem, describe the field where innovation in AI for PA occurs, and highlight the potentialities...
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Experience oriented enhancement of smartness for Internet of Things
PublikacjaIn this paper, we propose a novel approach, the Experience-Oriented Smart Things that allows experiential knowledge discovery, storage, involving, and sharing for Internet of Things. The main features, architecture, and initial experiments of this approach are introduced. Rather than take all the data produced by Internet of Things, this approach focuses on acquiring only interesting data for its knowledge discovery process. By...
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Optimising approach to designing kernel PCA model for diagnosis purposes with and without a priori known data reflecting faulty states
PublikacjaFault detection plays an important role in advanced control of complex dynamic systems since precise information about system condition enables efficient control. Data driven methods of fault detection give the chance to monitor the plant state purely based on gathered measurements. However, they especially nonlinear, still suffer from a lack of efficient and effective learning methods. In this paper we propose the two stages learning...
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AUTOMATIC LEARNING OF STRATEGY AND RULES IN CARD GAMES USING IMAGE FROM CAMERA
PublikacjaBelow work tries to answer a question: if it is possible to replace real human with computer system in social games. As a subject for experiments, card games were chosen, because they require a lot of player interaction (playing and taking cards), while their rules are easy to present in form of clear list of statements. Such a system, should allow real players to play without constant worrying about guiding or helping computer...
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A review of explainable fashion compatibility modeling methods
PublikacjaThe paper reviews methods used in the fashion compatibility recommendation domain. We select methods based on reproducibility, explainability, and novelty aspects and then organize them chronologically and thematically. We presented general characteristics of publicly available datasets that are related to the fashion compatibility recommendation task. Finally, we analyzed the representation bias of datasets, fashion-based algorithms’...
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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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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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A Bayesian regularization-backpropagation neural network model for peeling computations
PublikacjaA Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...
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Classifying Emotions in Film Music - A Deep Learning Approach
PublikacjaThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
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System bezpieczeństwa dla współpracującego robota przemysłowego na bazie kamer głębi
PublikacjaW artykule zarysowano problematykę robotyzacji małych przedsiębiorstw, w szczególności aspekt robotyzacji z uwzględnieniem robotów współpracujących. Szeroko omówiono zagadnienie robotów współpracujących oraz bezpieczeństwa człowieka podczas takiej współpracy. Przedstawiono również najbardziej popularne systemy bezpieczeństwa w odniesieniu do obowiązujących norm. W głównej części artykułu przedstawiono Cooperating Automaton System...
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Deep neural network architecture search using network morphism
PublikacjaThe paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...
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A survey of neural networks usage for intrusion detection systems
PublikacjaIn recent years, advancements in the field of the artificial intelligence (AI) gained a huge momentum due to the worldwide appliance of this technology by the industry. One of the crucial areas of AI are neural networks (NN), which enable commer‐ cial utilization of functionalities previously not accessible by usage of computers. Intrusion detection system (IDS) presents one of the domains in which neural networks are widely tested...
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Using water sources extent during inundation as a reliable predictor for vegetation zonation in a natural wetland floodplain
PublikacjaDistinctive zones of inundation water during floods were shown to originate from different sources in some major floodplains around the world. Recent research showed that the zonation of water in rivers and floodplains is related to vegetation patterns. In spite of this, water source zones were not used for vegetation modeling due to difficulties in their delineation. In this study, we used simulation results of a fully-coupled...
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Methodology for Performing Bathymetric Measurements of Shallow Waterbodies Using an UAV, and their Processing Based on the SVR Algorithm
PublikacjaState-of-art methods of bathymetric measurements for shallow waterbodies use Global Navigation Satellite System (GNSS) receiver, bathymetric Light Detection and Ranging (LiDAR) sensor or satellite imagery. Currently, photogrammetric methods with the application of Unmanned Aerial Vehicles (UAV) are gathering great importance. This publication aims to present step-by-step methodology for carrying out the bathymetric measurements...
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Methodology for Performing Bathymetric Measurements of Shallow Waterbodies Using an UAV, and their Processing Based on the SVR Algorithm
PublikacjaState-of-art methods of bathymetric measurements for shallow waterbodies use Global Navigation Satellite System (GNSS) receiver, bathymetric Light Detection and Ranging (LiDAR) sensor or satellite imagery. Currently, photogrammetric methods with the application of Unmanned Aerial Vehicles (UAV) are gathering great importance. This publication aims to present step-by-step methodology for carrying out the bathymetric measurements...
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Systematic Literature Review on Click Through Rate Prediction
PublikacjaThe ability to anticipate whether a user will click on an item is one of the most crucial aspects of operating an e-commerce business, and clickthrough rate prediction is an attempt to provide an answer to this question. Beginning with the simplest multilayer perceptrons and progressing to the most sophisticated attention networks, researchers employ a variety of methods to solve this issue. In this paper, we present the findings...
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Autoencoder application for anomaly detection in power consumption of lighting systems
PublikacjaDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
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Self-organising maps in the analysis of strains of human abdominal wall to identify areas of similar mechanical behaviour.
PublikacjaThe study refers to the application of a type of artificial neural network called the Self-Organising Map (SOM) for the identification of areas of the human abdominal wall that behave in a similar mechanical way. The research is based on data acquired during in vivo tests using the digital image correlation technique (DIC). The mechanical behaviour of the human abdominal wall is analysed during changing intra-abdominal pressure....
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Looking through the past: better knowledge retention for generative replay in continual learning
PublikacjaIn this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained...
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Comparison of 3D Point Cloud Completion Networks for High Altitude Lidar Scans of Buildings
PublikacjaHigh altitude lidar scans allow for rapid acquisition of big spatial data representing entire city blocks. Unfortunately, the raw point clouds acquired by this method are largely incomplete due to object occlusions and restrictions in scanning angles and sensor resolution, which can negatively affect the obtained results. In recent years, many new solutions for 3D point cloud completion have been created and tested on various objects;...
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Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks
PublikacjaThe presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods....
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublikacjaArtificial 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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Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublikacjaNematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...
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Analysis-by-synthesis paradigm evolved into a new concept
PublikacjaThis work aims at showing how the well-known analysis-by-synthesis paradigm has recently been evolved into a new concept. However, in contrast to the original idea stating that the created sound should not fail to pass the foolproof synthesis test, the recent development is a consequence of the need to create new data. Deep learning models are greedy algorithms requiring a vast amount of data that, in addition, should be correctly...
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Mispronunciation Detection in Non-Native (L2) English with Uncertainty Modeling
PublikacjaA common approach to the automatic detection of mispronunciation in language learning is to recognize the phonemes produced by a student and compare it to the expected pronunciation of a native speaker. This approach makes two simplifying assumptions: a) phonemes can be recognized from speech with high accuracy, b) there is a single correct way for a sentence to be pronounced. These assumptions do not always hold, which can result...
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Automated Classifier Development Process for Recognizing Book Pages from Video Frames
PublikacjaOne 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...