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Human verbal memory encoding is hierarchically distributed in a continuous processing stream
PublikacjaProcessing of memory is supported by coordinated activity in a network of sensory, association, and motor brain regions. It remains a major challenge to determine where memory is encoded for later retrieval. Here we used direct intracranial brain recordings from epilepsy patients performing free recall tasks to determine the temporal pattern and anatomical distribution of verbal memory encoding across the entire human cortex. High...
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Real and imaginary motion classification based on rough set analysis of EEG signals for multimedia applications
PublikacjaRough set-based approach to the classification of EEG signals of real and imaginary motion is presented. The pre-processing and signal parametrization procedures are described, the rough set theory is briefly introduced, and several classification scenarios and parameters selection methods are proposed. Classification results are provided and discussed with their potential utilization for multimedia applications controlled by the...
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A method for counting people attending large public events
PublikacjaThe algorithm for people counting in crowded scenes, based on the idea of virtual gate which uses optical flow method is presented. The concept and practical application of the developed algorithm under real conditions is depicted. The aim of the work is to estimate the number of people passing through entrances of a large sport hall. The most challenging problem was the unpredicted behavior of people while entering the building....
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Two-Rate Based Low-Complexity Variable Fractional-Delay FIR Filter Structures
PublikacjaThis paper considers two-rate based structures for variable fractional-delay (VFD) finite-length impulse response (FIR) filters. They are single-rate structures but derived through a two-rate approach. The basic structure considered hitherto utilizes a regular half-band (HB) linear-phase filter and the Farrow structure with linear-phase subfilters. Especially for wide-band specifications, this structure is computationally efficient...
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Estimating Traffic Intensity Employing Passive Acoustic Radar and Enhanced Microwave Doppler Radar Sensor
PublikacjaInnovative road signs that can autonomously display the speed limit in cases where the trac situation requires it are under development. The autonomous road sign contains many types of sensors, of which the subject of interest in this article is the Doppler sensor that we have improved and the constructed and calibrated acoustic probe. An algorithm for performing vehicle detection and tracking, as well as vehicle speed measurement,...
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Microscopic traffic simulation models for connected and automated vehicles (CAVs) – state-of-the-art
PublikacjaResearch on connected and automated vehicles (CAVs) has been gaining substantial momentum in recent years. However, thevast amount of literature sources results in a wide range of applied tools and datasets, assumed methodology to investigate thepotential impacts of future CAVs traffic, and, consequently, differences in the obtained findings. This limits the scope of theircomparability and applicability and calls for a proper standardization...
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A low complexity double-talk detector based on the signal envelope
PublikacjaA new algorithm for double-talk detection, intended for use in the acoustic echo canceller for voice communication applications, is proposed. The communication system developed by the authors required the use of a double-talk detection algorithm with low complexity and good accuracy. The authors propose an approach to doubletalk detection based on the signal envelopes. For each of three signals: the far-end speech, the microphone...
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Classification of Music Genres Based on Music Separation into Harmonic and Drum Components . Klasyfikacja gatunków muzycznych wykorzystująca separację instrumentów muzycznych
PublikacjaThis article presents a study on music genre classification based on music separation into harmonic and drum components. For this purpose, audio signal separation is executed to extend the overall vector of parameters by new descriptors extracted from harmonic and/or drum music content. The study is performed using the ISMIS database of music files represented by vectors of parameters containing music features. The Support Vector...
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Behavior Analysis and Dynamic Crowd Management in Video Surveillance System
PublikacjaA concept and practical implementation of a crowd management system which acquires input data by the set of monitoring cameras is presented. Two leading threads are considered. First concerns the crowd behavior analysis. Second thread focuses on detection of a hold-ups in the doorway. The optical flow combined with soft computing methods (neural network) is employed to evaluate the type of crowd behavior, and fuzzy logic aids detection...
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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublikacjaIdentification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable...
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Deep neural networks for human pose estimation from a very low resolution depth image
PublikacjaThe work presented in the paper is dedicated to determining and evaluating the most efficient neural network architecture applied as a multiple regression network localizing human body joints in 3D space based on a single low resolution depth image. The main challenge was to deal with a noisy and coarse representation of the human body, as observed by a depth sensor from a large distance, and to achieve high localization precision....
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Reversible Video Stream Anonymization for Video Surveillance Systems Based on Pixels Relocation and Watermarking
PublikacjaA method of reversible video image regions of interest anonymization for applications in video surveillance systems is described. A short introduction to theanonymization procedures is presented together with the explanation of its relation to visual surveillance. A short review of state of the art of sensitive data protection in media is included. An approach to reversible Region of Interest (ROI) hiding in video is presented,...
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Bass Enhancement Settings in Portable Devices Based on Music Genre Recognition
PublikacjaThe paper presents a novel approach to the Virtual Bass Synthesis (VBS) applied to mobile devices, called Smart VBS (SVBS). The proposed algorithm uses an intelligent, rule-based setting of bass synthesis parameters adjusted to the particular music genre. Harmonic generation is based on a nonlinear device (NLD) method with the intelligent controlling system adapting to the recognized music genre. To automatically classify music...
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Visual Lip Contour Detection for the Purpose of Speech Recognition
PublikacjaA method for visual detection of lip contours in frontal recordings of speakers is described and evaluated. The purpose of the method is to facilitate speech recognition with visual features extracted from a mouth region. Different Active Appearance Models are employed for finding lips in video frames and for lip shape and texture statistical description. Search initialization procedure is proposed and error measure values are...
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Music Mood Visualization Using Self-Organizing Maps
PublikacjaDue to an increasing amount of music being made available in digital form in the Internet, an automatic organization of music is sought. The paper presents an approach to graphical representation of mood of songs based on Self-Organizing Maps. Parameters describing mood of music are proposed and calculated and then analyzed employing correlation with mood dimensions based on the Multidimensional Scaling. A map is created in which...
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Fluctuation-enhanced scent sensing using a single gas sensor
PublikacjaWykrywanie zapachów podczas aromaterapii może być przeprowadzone za pomocą pojedynczego sensora gazów. W pracy rozważono efektywność detekcji zapachów olejków eterycznych za pomocą rezystancji DC oraz zjawisk fluktuacyjnych w tych sensorach, typu TGS2600,TGS2602,TGS823. Badania koncentrowały się na praktycznym zastosowaniu w aromaterapii do określania intensywności emitowanego zapachu. Opisano szczegółowo system do emisji zapachów.
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Fluctuation-enhanced scent sensing using a single gas sensor
PublikacjaScent or aroma sensing during aromatherapy can be carried out by applying only a single resistance gas sensor (TGS - Taguchi Gas Sensors). This paper considers the efficiency of detection of essential oils by DC resistance and its fluctuations observed in TGS sensors. A detailed study has been conducted for scents emitted by five popular essential oils using three sensor types (TGS 2600, TGS 2602, TGS 823). The research was focused...
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UPDRS tests for diagnosis of Parkinson's disease employing virtual-touchpad
PublikacjaThis paper presents a new approach to diagnosing Parkinson's disease. The progression of the disease can be measured by the UPDRS (Unified Parkinson Disease Rating Scale) scale which is used to evaluate motor and behavioral symptoms of Parkinson's disease. Hitherto the evaluation of the advancement of the disease in the UPDRS scale was made by a specialist through medical observation. The authors suggest a partial automation of...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublikacjaAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
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Musical Instrument Identification Using Deep Learning Approach
PublikacjaThe 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...