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Search results for: QUANTIZATION AWARE TRAINING
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Biometric identity verification
PublicationThis chapter discusses methods which are capable of protecting automatic speaker verification systems (ASV) from playback attacks. Additionally, it presents a new approach, which uses computer vision techniques, such as the texture feature extraction based on Local Ternary Patterns (LTP), to identify spoofed recordings. We show that in this case training the system with large amounts of spectrogram patches may be difficult, and...
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Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublicationIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
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Quantum Coherence as a Resource
PublicationThe coherent superposition of states, in combination with the quantization of observables, represents one of the most fundamental features that mark the departure of quantum mechanics from the classical realm. Quantum coherence in many-body systems embodies the essence of entanglement and is an essential ingredient for a plethora of physical phenomena in quantum optics, quantum information, solid state physics, and nanoscale thermodynamics....
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Investigation into MPI All-Reduce Performance in a Distributed Cluster with Consideration of Imbalanced Process Arrival Patterns
PublicationThe paper presents an evaluation of all-reduce collective MPI algorithms for an environment based on a geographically-distributed compute cluster. The testbed was split into two sites: CI TASK in Gdansk University of Technology and ICM in University of Warsaw, located about 300 km from each other, both connected by a fast optical fiber Ethernet-based 100 Gbps network (900 km part of the PIONIER backbone). Each site hosted a set...
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Food Classification from Images Using a Neural Network Based Approach with NVIDIA Volta and Pascal GPUs
PublicationIn the paper we investigate the problem of food classification from images, for the Food-101 dataset extended with 31 additional food classes from Polish cuisine. We adopted transfer learning and firstly measured training times for models such as MobileNet, MobileNetV2, ResNet50, ResNet50V2, ResNet101, ResNet101V2, InceptionV3, InceptionResNetV2, Xception, NasNetMobile and DenseNet, for systems with NVIDIA Tesla V100 (Volta) and...
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A CONTEXT IN RECOMMENDER SYSTEMS
PublicationRecommender systems aim to propose potentially interesting items to a user based on his preferences or previous interaction with the system. In the last decade, researcher found out that known recommendation techniques are not sufficient to predict user decisions. It has been noticed that user preferences strongly depend on the context in which he currently is. This raises new challenges for the researchers such as how to obtain...
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Active Learning Based on Crowdsourced Data
PublicationThe paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach. In the proposed solution, aimed at data engineers, the knowledge of the crowd serves as an oracle that is able to judge whether the given sample is informative or not. The proposed solution reduces the amount of work needed to annotate large sets of data. Furthermore, it allows a perpetual increase...
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Texture Features for the Detection of Playback Attacks: Towards a Robust Solution
PublicationThis paper describes the new version of a method that is capable of protecting automatic speaker verification (ASV) systems from playback attacks. The presented approach uses computer vision techniques, such as the texture feature extraction based on Local Ternary Patterns (LTP), to identify spoofed recordings. Our goal is to make the algorithm independent from the contents of the training set as much as possible; we look for the...
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Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublicationThe acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...
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Tinnitus Therapy Based on High-Frequency Linearization Principles - Preliminary Results
PublicationThe aim of this work is to present problems related to tinnitus symptoms, its pathogenesis, hypotheses on tinnitus causes, and therapy treatment to reduce or mask the phantom noise. In addition, the hypothesis on the existence of parasitic quantization that accompanies hearing loss has been recalled. Moreover, the paper describes a study carried out by the Authors with the application of high-frequency dither having specially formed...
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Massive Open Online Courses (MOOCs) in hospitality and tourism
PublicationThe tourism industry, interesting and challenging, faces structural human resource problems such as skills shortages and staff turnover, seasonality and a high percentage of small to medium enterprises whose employees have limited time for training or education. Large tourism enterprises often span countries and continents, such as hotel chains, airlines, cruise companies and car rentals, where the employees need similar training...
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Feature Reduction Using Similarity Measure in Object Detector Learning with Haar-like Features
PublicationThis paper presents two methods of training complexity reduction by additional selection of features to check in object detector training task by AdaBoost training algorithm. In the first method, the features with weak performance at first weak classifier building process are reduced based on a list of features sorted by minimum weighted error. In the second method the feature similarity measures are used to throw away that features...
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Performance improvement of NN based RTLS by customization of NN structure - heuristic approach
PublicationThe purpose of this research is to improve performance of the Hybrid Scene Analysis – Neural Network indoor localization algorithm applied in Real-time Locating System, RTLS. A properly customized structure of Neural Network and training algorithms for specific operating environment will enhance the system’s performance in terms of localization accuracy and precision. Due to nonlinearity and model complexity, a heuristic analysis...
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Top k Recommendations using Contextual Conditional Preferences Model
PublicationRecommender systems are software tools and techniques which aim at suggesting to users items they might be interested in. Context-aware recommender systems are a particular category of recommender systems which exploit contextual information to provide more adequate recommendations. However, recommendation engines still suffer from the cold-start problem, namely where not enough information about users and their ratings is available....
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Computer-Supported Polysensory Integration Technology for Educationally Handicapped Pupils
PublicationIn this paper, a multimedia system providing technology for hearing and visual attention stimulation is shortly presented. The system aims to support the development of educationally handicapped pupils. The system has been presented in the context of its configuration, architecture, and therapeutic exercise implementation issues. Results of pupils’ improvements after 8 weeks of training with the system are also provided. Training...
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Adaptive CAD-Model Construction Schemes
PublicationTwo advanced surrogate model construction techniques are discussed in this paper. The models employ radial basis function (RBF)interpolation scheme or artificial neural networks (ANN) with a new training algorithm. Adaptive sampling technique is applied withrespect to all variables. Histograms showing the quality of the models are presented. While the quality of RBF models is satisfactory, theperformance of the ANN models obtained...
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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 review of emotion recognition methods based on keystroke dynamics and mouse movements
PublicationThe paper describes the approach based on using standard input devices, such as keyboard and mouse, as sources of data for the recognition of users’ emotional states. A number of systems applying this idea have been presented focusing on three categories of research problems, i.e. collecting and labeling training data, extracting features and training classifiers of emotions. Moreover the advantages and examples of combining standard...
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Recognizing emotions on the basis of keystroke dynamics
PublicationThe article describes a research on recognizing emotional states on the basis of keystroke dynamics. An overview of various studies and applications of emotion recognition based on data coming from keyboard is presented. Then, the idea of an experiment is presented, i.e. the way of collecting and labeling training data, extracting features and finally training classifiers. Different classification approaches are proposed to be...
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Simple Measurement Method for Resistive Sensors Based on ADCs of Microcontrollers
PublicationA new, complete measurement method for resistance measurement of resistive sensors for systems based on microcontrollers equipped with analog-to-digital converters (ADCs) is proposed. The interface circuit consists of only four resistors, including a resistive sensor and a reference resistor, connected directly to the microcontroller pins. It is activated only during measurements, which significantly reduces power consumption....
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Color-based Detection of Bleeding in Endoscopic Images
PublicationIn this paper a color descriptor designed for bleeding detection in endoscopic images is proposed. The development of the algorithm was carried out on a representative training set of 36 images of bleeding and 25 clear images. Another 38 bleeding and 26 normal images were used in the final stage as a test set. All of the considered images were extracted from separate endoscopic examinations. The experiments include color distribution...
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Musical Instrument Identification Using Deep Learning Approach
PublicationThe work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related to musical instrument identification. It focuses on tasks performed, input type, algorithms employed, and metrics used. The paper starts with the background presentation, i.e., metadata...
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Towards Scalable Simulation of Federated Learning
PublicationFederated learning (FL) allows to train models on decentralized data while maintaining data privacy, which unlocks the availability of large and diverse datasets for many practical applications. The ongoing development of aggregation algorithms, distribution architectures and software implementations aims for enabling federated setups employing thousands of distributed devices, selected from millions. Since the availability of...
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Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia
PublicationW pracy doktorskiej podjęto problem realizacji algorytmów głębokiego uczenia w warunkach deficytu danych uczących. Głównym celem było opracowanie podejścia optymalizującego strukturę sieci neuronowej oraz zastosowanie uczeniu dwuetapowym, w celu uzyskania mniejszych struktur, zachowując przy tym dokładności. Proponowane rozwiązania poddano testom na zadaniu klasyfikacji znamion skórnych na znamiona złośliwe i łagodne. W pierwszym...
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Affective reactions to playing digital games
PublicationThe paper presents a study of emotional states during a gameplay. An experiment of two-player Tetris game is reported, followed by the analysis of the results - self-reported emotional states as well as physiological signals measurements interpretation. The study reveals the diversity of emotional reactions and concludes, that a representative player's emotional model is hard to define. Instead, an adaptive approach to emotion...
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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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Polski PR-owiec w świecie ponowoczesnym – wyniki badań i ich analiza. Poza dobrem i złem
PublicationW artykule analizuję wyniki badania Profesjonalizm public relations w Polsce, przeprowadzonego na potrzeby budowanego dokumentu Standardy profesjonalnego public relations – prezentowanego w tej pracy. Stawiam również pytanie o przyczynę częstych odpowiedzi respondentów „czasami” czy „nie mam zdania” i wykazuję niespójność systemów wartości respondentów zestawiając ich odpowiedzi na poszczególne pytania. Stawiam tezę, że niespójności...
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Model of emotions for game players
PublicationAffect-aware video games can respond to a game player's emotions. Such games seem to be more attractive for users. Therefore for that kind of games it is necessary to create a model of the player's emotions to know to which emotions the application should react. The paper describes different models of emotions. The questionnaire and experiment for video game players is presented. Some results of the tests are shown. Then the model...
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Spatial Modelling in Environmental Analysis and Civil Engineering
PublicationAs can be seen, Spatial Modelling in Environmental Analysis and Civil Engineering applies to a multitude of applications. In an attempt to bring the topic closer to potential readers, the special issue referred to security methods, optimization of calculations, conducting measurements and empirical tests. Each article has made an original contribution to the development of practical science that can be replicated by researchers...
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Train the trainer course
PublicationThis chapter presents the concept, evaluation and evaluation results for the train the trainer. This concept of train the trainers is prepared within Workpackage 5 of EU-funded project: MASTER BSR (Erasmus+ Strategic Partnership Programme). Due to the nature of adult learning the content is designed for the use of participatory methods (involved, active). This method uses various techniques of active learning e.g. group work,...
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Narzędzia treningu twórczości jako pomoc w kształceniu projektantów
PublicationKreatywność rozwijać. Na tym założeniu opiera się międzynarodowy program edukacyjny Odyssey of the Mind (Odyseja Umysłu). W programie zespoły młodych osób pracują metodą projektową, wykorzystując różnorodne techniki treningu twórczości, nad rozwiązaniem abstrakcyjnego problemu rozbieżnego. Część absolwentów programu wybiera kierunki kreatywne jako naturalną kontynuację procesu edukacji. Elementy treningu twórczości można wykorzystać...
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Creating new voices using normalizing flows
PublicationCreating realistic and natural-sounding synthetic speech remains a big challenge for voice identities unseen during training. As there is growing interest in synthesizing voices of new speakers, here we investigate the ability of normalizing flows in text-to-speech (TTS) and voice conversion (VC) modes to extrapolate from speakers observed during training to create unseen speaker identities. Firstly, we create an approach for TTS...
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Development and test of fex, a fingers extending exoskeleton for rehabilitation and regaining mobility
PublicationThis paper presents the design process of an exoskeleton for executing human fingers' extension movement for the rehabilitation procedures and as an active orthosis purposes, together with its first clinical usability tests of a robotic exoskeleton. Furthermore, the Fingers Extending eXoskeleton (FEX) is a serial, under-actuated mechanism capable of executing fingers' extension. FEX is based on the state-of-art FingerSpine serial...
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Akcelerator transformacji DCT do kompresji obrazu w sensorach wizyjnych
PublicationW komunikacie przedstawiono konfigurowalny cyfrowy akcelerator transformacji DCT przeznaczony dla enkodera wideo standardu H.264. Akcelerator realizuje także odwrotnątransformacjęDCT oraz kwantyzacjęi dekwantyzację. Akcelerator początkowo zaimplementowano w układzie FPGA. Zostałon pomyślnie zweryfikowany, a następnie zaimplementowany w układzie ASIC w technologii UMC 90 nm. Szczegółowe wyniki testów akceleratora ASIC zostały...
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Physics augmented classification of fNIRS signals
PublicationBackground. Predictive classification favours performance over semantics. In traditional predictive classification pipelines, feature engineering is often oblivious to the underlying phenomena. Hypothesis. In applied domains such as functional Near Infrared Spectroscopy (fNIRS), the exploitation of physical knowledge may improve the discriminative quality of our observation set. Aims. Give exemplary evidence that intervening the...
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Time travel without paradoxes: Ring resonator as a universal paradigm for looped quantum evolutions
PublicationA ring resonator involves a scattering process where a part of the output is fed again into the input. The same formal structure is encountered in the problem of time travel in a neighborhood of a closed timelike curve (CTC). We know how to describe quantum optics of ring resonators, and the resulting description agrees with experiment. We can apply the same formal strategy to any looped quantum evolution, in particular to the...
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Immersive Technologies that Aid Additive Manufacturing Processes in CBRN Defence Industry
PublicationTesting unique devices or their counterparts for CBRN (C-chemical, B-biological, R-radiological, N-nuclear) defense relies on additive manufacturing processes. Immersive technologies aid additive manufacturing. Their use not only helps understand the manufacturing processes, but also improves the design and quality of the products. This article aims to propose an approach to testing CBRN reconnaissance hand-held products developed...
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Towards bees detection on images: study of different color models for neural networks
PublicationThis paper presents an approach to bee detection in videostreams using a neural network classifier. We describe the motivationfor our research and the methodology of data acquisition. The maincontribution to this work is a comparison of different color models usedas an input format for a feedforward convolutional architecture appliedto bee detection. The detection process has is based on a neural...
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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublicationDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...
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Zastosowanie metody studium przypadku w kształceniu menedżerów
PublicationKształcenie z wykorzystaniem metod rozwiązywania problemów (problem-based learning) staje się coraz bardziej popularne na wszystkich poziomach kształcenia, również w edukacji biznesowej. Przykładem takiej metody jest studium przypadku (case study). Metoda studium przypadku pozwala na rozwijanie umiejętności i kompetencji wykorzystywanych przez menedżerów w ich pracy, np. umiejętności syntezy, identyfikacji problemów, czy podejmowania...
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Computer-assisted assessment of learning outcomes in the laboratory of metrology
PublicationIn the paper, didactic experience with broad and rapid continuous assessment of students’ knowledge, skills and competencies in the Laboratory of Metrology, which is an example of utilisation of assessment for learning, is presented. A learning management system was designed for manage, tracking, reporting of learning program and assessing learning outcomes. It has ability to provide with immediate feedback, which is used by the...
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PROJEKTOWANIE STANOWISK LABORATORYJNYCH WSPIERAJĄCYCH PROCES SZKOLENIA PRAKTYCZNEGO KADR MORSKICH DZIAŁU MASZYNOWEGO W ŻEGLUDZE MIĘDZYNARODOWEJ, PRZYBRZEŻNEJ I KRAJOWEJ
PublicationWithin the article a design offer of the Department of Ship and Power Plants of the Faculty of Ocean Engineering And Ship Technology at the Gdansk University of Technology has been presented. The offer concerns designing laboratory stations which might stand for the equipment of a didactic base of maritime educational centers i.e. maritime (naval) academies and schools as well as maritime affairs' professional training centers,...
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Strategie treningu neuronowego estymatora częstotliwości tonu krtaniowego z użyciem generatora syntetycznych samogłosek
PublicationW wielu zastosowaniach telekomunikacyjnych pojawia się problem przetwarzania lub analizy sygnału mowy, w ramach którego, często w obszarze podstawowych algorytmów, stosuje się estymator częstotliwości tonu krtaniowego. Estymator rozpatrywany w tej pracy bazuje na neuronowym klasyfikatorze podejmującym decyzje na podstawie częstotliwości oraz mocy chwilowej wyznaczanych w podpasmach analizowanego sygnału mowy. W pracy rozważamy...
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Generalization of Phylogenetic Matching Metrics with Experimental Tests of Practical Advantages
PublicationThe ability to quantify a dissimilarity of different phylogenetic trees is required in various types of phylogenetic studies, for example, such metrics are used to assess the quality of phylogeny construction methods and to define optimization criteria in supertree building algorithms. In this article, starting from the already described concept of matching metrics, we define three new metrics for rooted phylogenetic trees. One...
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Performance of FAN conception of traffic control in IP QoS networks
PublicationIn this paper we present the architectural implementation of Flow Aware Networking (FAN), a new approach for realizing QoS guarantees in the Internet. We also propose FAN traffic control algorithm which performs traffic control on flow level. Using the proposed FAN node model, we conduct simulation research to prove if FAN can be a new approach for realizing QoS guarantees. The basis of this research is finding a way to guarantee...
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Euro 2012 economic impact on host cities in Poland
PublicationThe UEFA European Championship (Euro) is among the world's most important sporting events staged nowadays. Apart from tremendous excitement among football fans, such a major event has a number of other implications, above all of economic nature. This study, as one of the few concerned with the Polish circumstances, is intended to determine what significance should be attributed to stage the Euro 2012 in Polish host cities. aware...
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Elements of six sigma methodoloygy in polish smes. the pomeranian region context
PublicationIn this article, it has been suggested that the effectiveness of the design and implementation of the process approach in the SMEs sector affects the effectiveness and efficiency of the application of elements of the Six Sigma ™ concept. The selected results of the research have been presented to answer the question to what extent small and medium-sized manufacturing, service and production - service companies in Pomeranian region...
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Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
PublicationThis paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublicationIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks
PublicationA method developed for parametrization of EEG signals gathered from participants with acquired brain injuries is shown. Signals were recorded during therapeutic session consisting of a series of computer assisted exercises. Data acquisition was performed in a neurorehabilitation center located in Poland. The presented method may be used for comparing the performance of subjects with acquired brain injuries (ABI) who are involved...