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Search results for: CONVOLUTIONAL NEURAL NETWORK, PEDESTRIAN DETECTION, ROBUSTNESS, STYLE-TRANSFER, DATA AUGMENTATION, UNCERTAINTY ESTIMATION
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Vident-synth: a synthetic intra-oral video dataset for optical flow estimation
Open Research DataWe introduce Vident-synth, a large dataset of synthetic dental videos with corresponding ground truth forward and backward optical flows and occlusion masks. It can be used for:
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Hybrid of Neural Networks and Hidden Markov Models as a modern approach to speech recognition systems
PublicationThe aim of this paper is to present a hybrid algorithm that combines the advantages ofartificial neural networks and hidden Markov models in speech recognition for control purpos-es. The scope of the paper includes review of currently used solutions, description and analysis of implementation of selected artificial neural network (NN) structures and hidden Markov mod-els (HMM). The main part of the paper consists of a description...
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Fashion Style & Popular Culture
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INDIVIDUAL TREE DETECTION FROM UAV LIDAR DATA IN A MIXED SPECIES WOODLAND
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Multi-Label Classification for AIS Data Anomaly Detection Using Wavelet Transform
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Data in Brief
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Estimation of Rician K-factor Values in Urban Terrain
PublicationThis paper presents results of Rician K-factor estimation from CDMA2000 downlink signals recorded in the area of medium city. Signal and data processing methods used to estimate fading parameters are also briefly described.
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Autonomous Ship Utility Model Parameter Estimation Utilising Extended Kalman Filter
PublicationIn this paper, a problem of autonomous ship utility model identification for control purposes is considered. In particular, the problem is formulated in terms of model parameter estimation (one-step-ahead prediction). This is a complex task due to lack of measurements of the parameter values, their time-variability and structural uncertainty introduced by the available models. In this work, authors consider and compare two utility...
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Customization of UWB 3D-RTLS Based on the New Uncertainty Model of the AoA Ranging Technique
PublicationThe increased potential and effectiveness of Real-time Locating Systems (RTLSs) substantially influence their application spectrum. They are widely used, inter alia, in the industrial sector, healthcare, home care, and in logistic and security applications. The research aims to develop an analytical method to customize UWB-based RTLS, in order to improve their localization performance in terms of accuracy and precision. The analytical...
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Port-based approach to distributed transfer function method
PublicationIn the paper there is presented an uniform, port-based approach to modeling of both lumped and distributed parameter systems. Port-based model of distributed system has been defined by application of distributed transfer function method (DTFM). The approach proposed combines versatility of port - based modeling and accuracy of distributed transfer function method. It enables to formulate appropriate input data for computer analysis...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Estimating the uncertainty of discharge coefficient predicted for oblique side weir using Monte Carlo method
PublicationSide weir is a hydraulic structure, which is used in irrigation systems to divert some water from main to side channel. It is installed at the entrance of the side channel to control and measure passing water into the side channel. Many studies provided side weir water surface profile and coefficient of discharge to measure water discharge diverted into the side channel. These studies dealt with different side weir shapes (rectangular,...
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Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running forward in...
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublicationIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
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Iron–Sulfur Cluster Biogenesis Chaperones: Evidence for Emergence of Mutational Robustness of a Highly Specific Protein–Protein Interaction
PublicationBiogenesis of iron–sulfur clusters (FeS) is a highly conserved process involving Hsp70 and J-protein chaperones. However, Hsp70 specialization differs among species. In most eukaryotes, including Schizosaccharomyces pombe, FeS biogenesis involves interaction between the J-protein Jac1 and the multifunctional Hsp70 Ssc1. But, in Saccharomyces cerevisiae and closely related species, Jac1 interacts with the specialized Hsp70 Ssq1,...
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Respiratory Rate Estimation Based on Detected Mask Area in Thermal Images
PublicationThe popularity of non-contact methods of measuring vital signs, particularly respiratory rate, has increased during the SARS-COV-2 pandemic. Breathing parameters can be estimated by analysis of temperature changes observed in thermal images of nostrils or mouth regions. However, wearing virus-protection face masks prevents direct detection of such face regions. In this work, we propose to use an automatic mask detection approach...
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A study of nighttime vehicle detection algorithms
Open Research DataThis dataset is from my master's thesis "A study of nighttime vehicle detection algorithms". It contains both raw data and preprocessed dataset ready to use. In the pictures below you can see how images were annotated.
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Data Analysis in Bridge of Data
PublicationThe chapter presents the data analysis aspects of the Bridge of Data project. The software framework used, Jupyter, and its configuration are presented. The solution’s architecture, including the TRYTON supercomputer as the underlying infrastructure, is described. The use case templates provided by the Stat-reducer application are presented, including data analysis related to spatial points’ cloud-, audio- and wind-related research.
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Optimal Selection of Input Features and an Acompanying Neural Network Structure for the Classification Purposes - Skin Lesions Case Study
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Soft-decision schemes for radar estimation of elevation at low grazing angles
PublicationIn modern radars, the problem of estimating elevation angle at low grazing angles is typically solved using superresolution techniques. These techniques often require one to provide an estimate of the number of waveforms impinging the array, which one can accomplish using model selection techniques. In this paper, we investigate the performance of an alternative approach, based on the Bayesian-like model averaging. The Bayesian...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublicationThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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A simplified energy dissipation based model of heat transfer for post-dryout flow boiling
Publicationmodel for post dryout mist flow heat transfer is presented based on considerations of energy dissipation in the flow. The model is an extension of authors own model developed earlier for saturated and subcooled flow boiling. In the former version of the model the heat transfer coefficient for the liquid singlephase convection as a reference was used, due to the lack of the appropriate model for heat transfer coefficient for the...
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Transmission Protocol Simulation Framework For The Resource-Constrained Wireless Sensor Network
PublicationIn this paper a prototype framework for simulation of wireless sensor network and its protocols are presented. The framework simulates operation of a sensor network with data transmission, which enables simultaneous development of the sensor network software, its hardware and the protocols for wireless data transmission. An advantage of using the framework is converging simulation with the real software. Instead of creating...
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The role and importance of WIMAX mobile system as a high-performance data transfer technology in wireless sensor networks for wide area monitoring applications
PublicationThe study discuses basic features and functional design of WiMAX Mobile system, based on the IEEE 802.16e (Release 1.5 Rev. 2.0) standard. The analysis has been made in terms of ability to use this system to transmit video stream related to monitoringof large agglomeration areas. What is more, the study includes comparison of technical parameters of WiMAX Mobile system with competitive systems such as: HSPA+ and UMTS-LTE, which...
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Electrical and noise responses of carbon nanotube networks enhanced by UV light for detection of organic gases (ethanol, acetone)
Open Research DataCarbon nanotube networks of different optical transparencies were investigated via resistance and 1/f noise measurements for detection of ethanol and acetone. The sensor resistive and noise responses were collected for dark and UV-assisted conditions, revealing the improvement in sensor sensitivity and limit of detection after applying UV light (275...
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Ryszard Katulski prof. dr hab. inż.
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A method of the UMTS-FDD network design based on universal load characteristics
PublicationIn the paper an original method of the UMTS radio network design was presented. The method is based on simple way of capacity-coverage trade-off estimation for WCDMA/FDD radio interface. This trade-off is estimated by using universal load characteristics and normalized coverage characteristics. The characteristics are useful for any propagation environment as well as for any service performance requirements. The practical applications...
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Transfer(Spain)
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Cross-layer integration of network mechanisms for increasing efficiency of multimedia session support in IEEE 802.11s environment
PublicationWith an IEEE 802.11 wireless networks operating in Point-to-Multipoint mode being the most popular WLAN access technology employed today, it can be expected that a Wireless Mesh Network (WMN) based on the technology can provide significant advantages for such network systems. The IEEE 802.11s standard amendment provides the comprehensive set of mechanisms required to implement and deploy a WMN utilizing this widely popular technology....
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Data Mining 2022/2023
e-Learning CoursesThis is a web page for our course in Data Mining.
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Data Mining 2021/2022
e-Learning CoursesThis is a web page for our course in Data Mining.
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Experimental Study of the Influence of Noise Level on the Uncertainty Value in a Measurement System Containing an Analog-to-Digital Converter
Open Research DataFor newly developed measuring systems it is easy to estimate type B uncertainties based on the technical data of the measuring modules applied. However, it is difficult to estimate A type un-certainties due to the unknown type and level of interferences infiltrating into the measuring sys-tem. This is a particularly important problem for measurements...
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Collaborative Data Acquisition and Learning Support
PublicationWith the constant development of neural networks, traditional algorithms relying on data structures lose their significance as more and more solutions are using AI rather than traditional algorithms. This in turn requires a lot of correctly annotated and informative data samples. In this paper, we propose a crowdsourcing based approach for data acquisition and tagging with support for Active Learning where the system acts as an...
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User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
PublicationIn this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublicationA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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Analytical model with non-adiabatic effects for pressure drop and heat transfer during boiling and condensation flows in conventional channels and minichannels
PublicationIn the paper a method developed earlier by authors is applied to calculations of pressure drop and heat transfer coefficient for boiling flow and condensation flow with account of non- adiabatic effects for some recent data collected from literature. The first effect, the modification of interface shear stresses in annular flow pattern is considered through incorporation of the so called "blowing parameter". The mechanism of...
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Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublicationThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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FPGA-Based Real-Time Implementation of Detection Algorithm for Automatic Traffic Surveillance Sensor Network
PublicationArtykuł opisuje sprzętową implementację w układzie FPGA algorytmu wykrywającego pojazdy, przeznaczonego do zastosowania w autonomicznej sieci sensorowej. Zadaniem algorytmu jest detekcja poruszających się pojazdów w obrazie z kamery pracującej w czasie rzeczywistym. Algorytm ma na celu oszacowanie parametrów ruchu ulicznego, takich jak liczba pojazdów, ich kierunek ruchu i przybliżona prędkość, przy wykorzystaniu sprzętu sieci...
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Evaluation of Facial Pulse Signals Using Deep Neural Net Models
PublicationThe reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...
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Transmission protocol simulation framework for the resource-constrained sensor network
PublicationIn this paper the simulation framework for simulation of the sensor network protocol is presented. The framework enables the simultaneous development of the sensor network software and the protocol for the wireless data transmission. The advantage of using the framework is the convergence of the simulation with the real software, because the same software is used in real sensor network nodes and in the simulation framework. The...
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Evaluating Accuracy of Respiratory Rate Estimation from Super Resolved Thermal Imagery
PublicationNon-contact estimation of Respiratory Rate (RR) has revolutionized the process of establishing the measurement by surpassing some issues related to attaching sensors to a body, e.g. epidermal stripping, skin disruption and pain. In this study, we perform further experiments with image processing-based RR estimation by using various image enhancement algorithms. Specifically, we employ Super Resolution (SR) Deep Learning (DL) network...
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Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublicationIn the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...
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Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a multivariate nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running...
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Uncertainty of mass flow measurement using centric and eccentric orifice for Reynolds number in the range 10,000 ≤ Re ≤ 20,000
PublicationThe article analyses the impact of the Reynolds number on the estimated uncertainty of the mass flow rate measurement using an orifice plate. The objects of the research were two types of orifices: centric (ISA) and eccentric, with the diameter ratio β = 0.5. Studies were performed by Monte Carlo simulation and experiments for Reynolds numbers in the range 10,000 ≤ Re ≤ 20,000. The obtained results have shown that for both orifice...
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Qualitative data analysis methods
e-Learning CoursesThis is the continuation of Qualitatative Data Analysis Methods course provided online
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Neural Graph Collaborative Filtering: Analysis of Possibilities on Diverse Datasets
PublicationThis paper continues the work by Wang et al. [17]. Its goal is to verify the robustness of the NGCF (Neural Graph Collaborative Filtering) technique by assessing its ability to generalize across different datasets. To achieve this, we first replicated the experiments conducted by Wang et al. [17] to ensure that their replication package is functional. We received sligthly better results for ndcg@20 and somewhat poorer results for...
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Radiation Detection Technology and Methods
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Data librarian and data steward – new tasks and responsibilities of academic libraries in the context of Open Research Data implementation in Poland
PublicationThesis/Objective – The policy of Open Access (OA) for researching resources in Europe has been implemented for more than 10 years. The first recommendations concerning providing OA to scientific materials were defined during the implementation of the 7th Framework Programme. Introducing another set of recommendations concerning OA to research data was the next stage. The recommendations were transformed into obligations under the...