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Wyniki wyszukiwania dla: CONVOLUTIONAL NEURAL NETWORK
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublikacjaThis work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...
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Wstępne wyniki badań dostępności sieci ASG-Eupos podczas inwentaryzacji trasy kolejowej Kościerzyna - Kartuzy = Preliminary research results of ASG-Eupos network availability during surveying of Kościerzyna-Kartuzyrailway route
PublikacjaW artykule przedstawiono wyniki pomiarów dostępności określonej wartości błędu współrzędnych, wyznaczonych przy wykorzystaniu sieci ASG-EUPOS, uzyskane podczas pomiarów inwentaryzacyjnych testowego odcinka linii kolejowej. Pomiary z wykorzystaniem4 odbiorników GNSS przeprowadzono w miesiącu lutym bieżącego roku na odcinku trasy kolejowej Kościerzyna - Kartuzy. Program badań zakładał montaż, na pokładzie platformy kolejowej napędzanej...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublikacjaAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublikacjaIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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LSTM-based method for LOS/NLOS identification in an indoor environment
PublikacjaDue to the multipath propagation, harsh indoor environment significantly impacts transmitted signals which may adversely affect the quality of the radiocommunication services, with focus on the real-time ones. This negative effect may be significantly reduced (e.g. resources management and allocation) or compensated (e.g. correction of position estimation in radiolocalisation) by the LOS/NLOS identification algorithm. This paper...
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Vehicle classification based on soft computing algorithms
PublikacjaExperiments and results regarding vehicle type classification are presented. Three classes of vehicles are recognized: sedans, vans and trucks. The system uses a non-calibrated traffic camera, therefore no direct vehicle dimensions are used. Various vehicle descriptors are tested, including those based on vehicle mask only and those based on vehicle images. The latter ones employ Speeded Up Robust Features (SURF) and gradient images...
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The trajectories of the financial crisis of companies at risk of bankruptcy
PublikacjaThis article concerns the assessment of the trajectory of the collapse of enterprises in Central Europe. The author has developed a model of a Kohonen artificial neural network. This model was used to determine 6 different classes of risk and was allowed to graphically determine the 5- to 10-year trajectory of going bankrupt. The study used data on 140 companies listed on the Warsaw Stock Exchange. This population was divided into...
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Optimized Computational Intelligence Model for Estimating the Flexural Behavior of Composite Shear Walls
PublikacjaThis article presents a novel approach to estimate the flexural capacity of reinforced concrete-filled composite plate shear walls using an optimized computational intelligence model. The proposed model was developed and validated based on 47 laboratory data points and the Transit Search (TS) optimization algorithm. Using 80% of the experimental dataset, the optimized model was selected by determining the unknown coefficients of...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Pancreatic neuroendocrine neoplasms — update of the diagnostic and therapeutic guidelines (recommended by the Polish Network of Neuroendocrine Tumours) [Nowotwory neuroendokrynne trzustki — uaktualnione zasady diagnostyki i leczenia (rekomendowane przez Polską Sieć Guzów Neuroendokrynych)]
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Serum levels of IL-6, IL-8 and CRP as prognostic factors in epithelial ovarian cancer
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Usefulness of selected laboratory markers in ulcerative colitis
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Composition Patterns of Contemporary Polish Residential Building Facades
PublikacjaThis study aims to define the types of composition patterns of contemporary Polish multi-family building facades. The authors define the compositional patterns to determine their frequency. Analyses carried out on the basis of photos and visualizations of 113 examples of architecture from Poland identified groups of common features of facades. Statistical analyses of these features resulted in six types of compositions. Clear differences...
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublikacjaThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publikacja—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
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Colorectal neuroendocrine neoplasms — update of the diagnostic and therapeutic guidelines (recommended by the Polish Network of Neuroendocrine Tumours) [Nowotwory neuroendokrynne jelita grubego — uaktualnione zasady diagnostyki i leczenia (rekomendowane przez Polską Sieć Guzów Neuroendokrynych)]
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Adaptive Hounsfield Scale Windowing in Computed Tomography Liver Segmentation
PublikacjaIn computed tomography (CT) imaging, the Hounsfield Unit (HU) scale quantifies radiodensity, but its nonlinear nature across organs and lesions complicates machine learning analysis. This paper introduces an automated method for adaptive HU scale windowing in deep learning-based CT liver segmentation. We propose a new neural network layer that optimizes HU scale window parameters during training. Experiments on the Liver Tumor...
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TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublikacjaTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
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Behavioral state classification in epileptic brain using intracranial electrophysiology
PublikacjaOBJECTIVE: Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. APPROACH: Data from seven patients (age [Formula: see text], 4 women) who underwent intracranial depth electrode...
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Effects of chronic neuroleptic treatment on dopamine release: Insights from studies using 3-methoxytyramine
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Poor evidence for depolarization block but uncoupling of nigral from striatal dopamine metabolism after chronic haloperidol treatment in the rat
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Modeling human thinking about similarities by neuromatrices in the perspective of fuzzy logic
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Determination of the impact indicators of electromagnetic interferences on computer information systems
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BP-EVD: Forward Block-Output Propagation for Efficient Video Denoising
PublikacjaDenoising videos in real-time is critical in many applications, including robotics and medicine, where varying light conditions, miniaturized sensors, and optics can substantially compromise image quality. This work proposes the first video denoising method based on a deep neural network that achieves state-of-the-art performance on dynamic scenes while running in real-time on VGA video resolution with no frame latency. The backbone...
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Dynamic Bankruptcy Prediction Models for European Enterprises
PublikacjaThis manuscript is devoted to the issue of forecasting corporate bankruptcy. Determining a firm’s bankruptcy risk is one of the most interesting topics for investors and decision-makers. The aim of the paper is to develop and to evaluate dynamic bankruptcy prediction models for European enterprises. To conduct this objective, four forecasting models are developed with the use of four different methods—fuzzy sets, recurrent and...
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MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS
PublikacjaIn this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones - the healthy blood cells (erythrocytes) and the pathologic (echinocytes). The separated blood cells are analyzed in terms of their most important features by the eigenfaces method. The features are the...
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublikacjaA 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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Fragmentation of Hydrographic Big Data Into Subsets During Reduction Process
PublikacjaThe article presented problems of fragmentation of hydrographic big data into smaller subsets during reduction process. Data reduction is a processing of reduce the value of the data set, in order to make them easier and more effective for the goals of the analysis. The main aim of authors is to create new reduction method. The article presented the first stage of this method – fragmentation of bathymetric data into subsets. It...
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Deep learning for recommending subscription-limited documents
PublikacjaDocuments recommendation for a commercial, subscription-based online platform is important due to the difficulty in navigation through a large volume and diversity of content available to clients. However, this is also a challenging task due to the number of new documents added every day and decreasing relevance of older contents. To solve this problem, we propose deep neural network architecture that combines autoencoder with...
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Instance segmentation of stack composed of unknown objects
PublikacjaThe article reviews neural network architectures designed for the segmentation task. It focuses mainly on instance segmentation of stacked objects. The main assumption is that segmentation is based on a color image with an additional depth layer. The paper also introduces the Stacked Bricks Dataset based on three cameras: RealSense L515, ZED2, and a synthetic one. Selected architectures: DeepLab, Mask RCNN, DEtection TRansformer,...
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Estimation of the Ultimate Strength of FRP Strips-to-Masonry Substrates Bond
PublikacjaFiber-Reinforced Polymers (FRP) were developed as a new method over the past decades due to their many beneficial mechanical properties, and they are commonly applied to strengthen masonry structures. In this paper, the Artificial Neural Network (ANN), K-fold Cross-Validation (KFCV) technique, Multivariate Adaptive Regression Spline (MARS) method, and M5 Model Tree (M5MT) method were utilized to predict the ultimate strength of...
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Embedded Representations of Wikipedia Categories
PublikacjaIn this paper, we present an approach to building neural representations of the Wikipedia category graph. We test four different methods and examine the neural embeddings in terms of preservation of graphs edges, neighborhood coverage in representation space, and their influence on the results of a task predicting parent of two categories. The main contribution of this paper is application of neural representations for improving the...
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Automated hearing loss type classification based on pure tone audiometry data
PublikacjaHearing problems are commonly diagnosed with the use of tonal audiometry, which measures a patient’s hearing threshold in both air and bone conduction at various frequencies. Results of audiometry tests, usually represented graphically in the form of an audiogram, need to be interpreted by a professional audiologist in order to determine the exact type of hearing loss and administer proper treatment. However, the small number of...
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A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks
PublikacjaThe visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases...
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Gastroduodenal neuroendocrine neoplasms including gastrinoma — update of the diagnostic and therapeutic guidelines (recommended by the Polish Network of Neuroendocrine Tumours) [Nowotwory neuroendokrynne żołądka i dwunastnicy z uwzględnieniem gastrinoma — uaktualnione zasady postępowania (rekomendowane przez Polską Sieć Guzów Neuroendokrynnych)]
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Human-Computer Interface Based on Visual Lip Movement and Gesture Recognition
PublikacjaThe multimodal human-computer interface (HCI) called LipMouse is presented, allowing a user to work on a computer using movements and gestures made with his/her mouth only. Algorithms for lip movement tracking and lip gesture recognition are presented in details. User face images are captured with a standard webcam. Face detection is based on a cascade of boosted classifiers using Haar-like features. A mouth region is located in...
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Food analysis using artificial senses.
PublikacjaNowadays, consumers are paying great attention to the characteristics of food such as smell, taste, and appearance. This motivates scientists to imitate human senses using devices known as electronic senses. These include electronic noses, electronic tongues, and computer vision. Thanks to the utilization of various sensors and methods of signal analysis, artificial senses are widely applied in food analysis for process monitoring...
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IFE: NN-aided Instantaneous Pitch Estimation
PublikacjaPitch estimation is still an open issue in contemporary signal processing research. Nowadays, growing momentum of machine learning techniques application in the data-driven society allows for tackling this problem from a new perspective. This work leverages such an opportunity to propose a refined Instantaneous Frequency and power based pitch Estimator method called IFE. It incorporates deep neural network based pitch estimation...
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublikacjaTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublikacjaBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublikacjaThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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Neuroendocrine neoplasms of the small intestine and the appendix — update of the diagnostic and therapeutic guidelines (recommended by the Polish Network of Neuroendocrine Tumours) [Nowotwory neuroendokrynne jelita cienkiego i wyrostka robaczkowego — uaktualnione zasady diagnostyki i leczenia (rekomendowane przez Polską Sieć Guzów Neuroendokrynnych)]
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Update of the diagnostic and therapeutic guidelines for gastro-entero-pancreatic neuroendocrine neoplasms (recommended by the Polish Network of Neuroendocrine Tumours) [Aktualizacja zaleceń ogólnych dotyczących postępowania diagnostyczno-terapeutycznego w nowotworach neuroendokrynnych układu pokarmowego (rekomendowane przez Polską Sieć Guzów Neuroendokrynnych)]
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Thermal Image Processing for Respiratory Estimation from Cubical Data with Expandable Depth
PublikacjaAs healthcare costs continue to rise, finding affordable and non-invasive ways to monitor vital signs is increasingly important. One of the key metrics for assessing overall health and identifying potential issues early on is respiratory rate (RR). Most of the existing methods require multiple steps that consist of image and signal processing. This might be difficult to deploy on edge devices that often do not have specialized...
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Standard of living in Poland at regional level - classification with Kohonen self-organizing maps
PublikacjaThe standard of living is spatially diversified and its analyzes enable shaping regional policy. Therefore, it is crucial to assess the standard of living and to classify regions due to their standard of living, based on a wide set of determinants. The most common research methods are those based on composite indicators, however, they are not ideal. Among the current critiques moved to the use of composite...
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Prediction of the Biogenic Amines Index of Poultry Meat Using an Electronic Nose
PublikacjaThe biogenic amines index of fresh chicken meat samples during refrigerated storage was predicted based on the headspace analysis using an electronic nose equipped with an array of electrochemical sensors. The reference biogenic amines index values were obtained using dispersive liquid–liquid microextraction–gas chromatography–mass spectrometry. A prototype electronic nose with modular construction and a dedicated sample chamber...
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Mixed-use buildings as the basic unit that shapes the housing environment of smart cities of the future
PublikacjaThe contemporary approach to creating the residential function is confronted with the trend of increasing the volume of buildings and expectations regarding the future urban environment focused on sustainable development. This paper presents an overview of the residential structure in the context of defined thematic scopes. Namely, it is a systemic approach to the problem of designing mixed-use buildings which create a modern residential...
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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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An electronic nose for quantitative determination of gas concentrations
PublikacjaThe practical application of human nose for fragrance recognition is severely limited by the fact that our sense of smell is subjective and gets tired easily. Consequen tly, there is considerable need for an instrument that can be a substitution of the human sense of smell. Electronic nose devices from the mid 1980s are used in growing number of applications. They comprise an array of several electrochemical gas sensors...
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The Development of a Combined Method to Quickly Assess Ship Speed and Fuel Consumption at Different Powertrain Load and Sea Conditions
PublikacjaDecision support systems (DSS) recently have been increasingly in use during ships operation. They require realistic input data regarding different aspects of navigation. To address the optimal weather routing of a ship, which is one of the most promising field of DSS application, it is necessary to accurately predict an actually attainable speed of a ship and corresponding fuel consumption at given loading conditions and predicted...