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Wyniki wyszukiwania dla: neural network architecture search
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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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Sterowanie optyczną siecią wielodomenową z hierarchiczną strukturą płaszczyzn sterowania
PublikacjaW artykule przedstawiono problem sterowania wielodomenową siecią optyczną z hierarchiczną strukturą płaszczyzn sterowania. Autorzy proponują wykorzystanie koncepcji sieci ASON/GMPLS, która spełnia wymagania nowoczesnych sieci optycznych, a jednocześnie umożliwia sterowanie wielodomenową siecią z gwarancją jakości usług. W artykule zaproponowano algorytm sterowania z gwarancją jakości, którego efektywność zweryfikowano metodą symulacji...
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Technical Engine for Democratization of Modeling, Simulations, and Predictions
PublikacjaComputational science and engineering play a critical role in advancing both research and daily-life challenges across almost every discipline. As a society, we apply search engines, social media, and se- lected aspects of engineering to improve personal and professional growth. Recently, leveraging such aspects as behavioral model analysis, simulation, big data extraction, and human computation is gain- ing momentum. The nexus...
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Design of Cost-Efficient Optical Fronthaul for 5G/6G Networks: An Optimization Perspective
PublikacjaCurrently, 5G and the forthcoming 6G mobile communication systems are the most promising cellular generations expected to beat the growing hunger for bandwidth and enable the fully connected world presented by the Internet of Everything (IoE). The cloud radio access network (CRAN) has been proposed as a promising architecture for meeting the needs and goals of 5G/6G (5G and beyond) networks. Nevertheless, the provisioning of cost-efficient...
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Delivery of Ancillary Services in Distribution Power Systems
PublikacjaOne of the technical and organizational challenges the power system faces in deregulated market conditions is to organize an ancillary services market. The growing share of distributed generation of variable (intermittent) energy sources and a change in the market position of consumers, causes the demand for distributed delivery of ancillary services. For this purpose, it is sought to use the ability of the regulatory measures:...
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Driver fatigue detection method based on facial image analysis
PublikacjaNowadays, ensuring road safety is a crucial issue that demands continuous development and measures to minimize the risk of accidents. This paper presents the development of a driver fatigue detection method based on the analysis of facial images. To monitor the driver's condition in real-time, a video camera was used. The method of detection is based on analyzing facial features related to the mouth area and eyes, such as...
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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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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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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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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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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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Towards Cancer Patients Classification Using Liquid Biopsy
PublikacjaLiquid biopsy is a useful, minimally invasive diagnostic and monitoring tool for cancer disease. Yet, developing accurate methods, given the potentially large number of input features, and usually small datasets size remains very challenging. Recently, a novel feature parameterization based on the RNA-sequenced platelet data which uses the biological knowledge from the Kyoto Encyclopedia of Genes and Genomes, combined with a classifier...
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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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Photos of LEGO bricks
Dane BadawczeRandom photos of the following LEGO bricks: 2419, 2450, 3022, 3031, 4070, 30357, 41682, 44570, 47998, 52107, 54383, 54384, 64799, 87609, 93274, 99206, 99781. The bricks were placed on a white sheet of paper, the photos were taken by hand, using Huawei P20 PRO camera positioned above the bricks. The photos were taken with and without flashlight. The...
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Charge-assisted N(+)–H···(−)S hydrogen bonds in the crystal structure of selected diammonium thiophenolates.
PublikacjaNew salts of thiophenol with three flexible aliphatic diamines H2N(CH2)nNH2 (n = 2, 4 and 6) have been synthesized and characterized by elemental analyses, IR spectroscopy and X-ray crystallography in order to analyze their supramolecular architecture. Structural analyses indicate that in the crystals, proton transfer has occurred, with the –SH group giving (+)N–H···S(−) hydrogen bonding interaction. The structure of compound 1...
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Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublikacjaIntroduction: Intracranial hemorrhage detection in 3D Computed Tomography (CT) brain images has gained more attention in the research community. The major issue to deal with the 3D CT brain images is scarce and hard to obtain the labelled data with better recognition results. Methods: To overcome the aforementioned problem, a new model has been implemented in this research manuscript. After acquiring the images from the Radiological...
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On-line Search in Two-Dimensional Environment
PublikacjaWe consider the following on-line pursuit-evasion problem. A team of mobile agents called searchers starts at an arbitrary node of an unknown network. Their goal is to execute a search strategy that guarantees capturing a fast and invisible intruder regardless of its movements using as few searchers as possible. As a way of modeling two-dimensional shapes, we restrict our attention to networks that are embedded into partial grids:...
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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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Wirtualne sieci 5G, NGN i następne. Radioinformatyczna metamorfoza sieci komórkowych
PublikacjaPrzedstawiono problematykę ewolucyjnej, a w zasadzie rewolucyjnej, metamorfozy komórkowych systemów radiokomunikacyjnych w kontekście architektury sieci 5G, zasad jej działania oraz nowych możliwości implementacyjnych usług sieci NGN. Artykuł dotyczy w szczególności istoty działania sieci 5G, łączącej w sobie cechy sieci radiokomunikacyjnych poprzednich generacji, zwłaszcza 4G, oraz nowe właściwości charakterystyczne dla 5G. Dotyczą...
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Training of Deep Learning Models Using Synthetic Datasets
PublikacjaIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening
PublikacjaFamilial hypercholesterolemia (FH) is a highly undiagnosed disease. Among FH patients, the onset of premature coronary artery disease is 13 times higher than in the general population. Early diagnosis and treatment is essential to prevent cardiovascular diseases and their complications, and to prolong life. One of the clinical criteria of FH is the occurrence of a corneal arcus (CA) among patients, especially those under 45 years...
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Simple and low-cost wireless voting system
PublikacjaThis paper presents the concept of a simple and low-cost wireless voting system working in the 868 MHz frequency band. The described system is dedicated to general shareholders assemblies but it can be easily adapted for other applications. The main advantage is its simplicity and mobility as it consists solely of three components - voting modules, a base station and a PC application from which the whole system is mamaged. This...
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Simple and low-cost wireless voting system
PublikacjaThis paper presents the concept of a simple and low-cost wireless voting system working on the 868 MHz frequency band. Described system is dedicated to general shareholders assemblies but it can be easily adapted for other applications. The main advantage is its simplicity and mobility as it consists solely of three components - voting modules, base station and a PC application from which the whole system is managed. This architecture...
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Mechanizmy bezpieczeństwa w strefie C systemu netBaltic
PublikacjaW artykule zaprezentowano rozwiązania zaimplementowane do zabezpieczania komunikacji w warunkach sporadycznej i nieciągłej łączności (Delay Tolerant Networking – DTN) w systemie netBaltic - charakterystycznej dla strefy C tego systemu. Ze względu na dużą różnorodność rozważanych mechanizmów komunikacyjnych, architektura bezpieczeństwa całego systemu została podzielona na kilka elementów – infrastrukturę klucza publicznego (PKI),...
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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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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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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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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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More Than just Antioxidants: Redox-Active Components and Mechanisms Shaping Redox Signalling Network
PublikacjasettingsOrder Article Reprints This is an early access version, the complete PDF, HTML, and XML versions will be available soon. Open AccessReview More Than just Antioxidants: Redox-Active Components and Mechanisms Shaping Redox Signalling Network by Monika Kuczyńska,Patrycja Jakubek andAgnieszka Bartoszek *ORCID Faculty of Chemistry, Gdańsk University of Technology, 80-233 Gdańsk, Poland * Author to whom correspondence should...
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Improved-Efficacy Optimization of Compact Microwave Passives by Means of Frequency-Related Regularization
PublikacjaElectromagnetic (EM)-driven optimization is an important part of microwave design, especially for miniaturized components where the cross-coupling effects in tightly arranged layouts make traditional (e.g., equivalent network) representations grossly inaccurate. Efficient parameter tuning requires reasonably good initial designs, which are difficult to be rendered for newly developed structures or when re-design for different operating...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublikacjaThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Diagnostyka łożysk silnika indukcyjnego na podstawie prądu zasilającego przy użyciu sztucznych sieci neuronowych
PublikacjaW artykule zawarto wyniki badań dotyczące diagnostyki łożysk silnika indukcyjnego na podstawie pomiarów prądu zasilającego z wyko-rzystaniem sztucznych sieci neuronowych. Zaprezentowano wyniki uczenia sieci oraz rezultaty testów przeprowadzonych na danych spoza zbioru uczącego. Badania wykonane zostały na obiektach z celowo wprowadzonymi uszkodzeniami łożysk. Przedstawiona nowa koncepcja zakłada użycie zestawu sieci neuronowych...
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Gustav Oelsner i Hugo Althoff. W poszukiwaniu godnych warunków zamieszkania w Altonie i Gdańsku
PublikacjaCelem artykułu jest porównanie aktywności zawodowej dwóch architektów miejskich odpowiedzialnych za przestrzenny i architektoniczny rozwój Gdańska i Altony - Hugona Althoffa i Gustava Oelsnera, oraz porównanie architektury i urbanistyki modernistycznych osiedli socjalnych. Celem porównania jest zbadanie, w jakim stopniu lokalne uwarunkowania i tradycja mogą być nośnikiem uniwersalnych ideałów modernizmu i indywidualnej ekspresji...
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublikacjaAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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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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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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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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Detecting Objects of Various Categories in Optical Remote Sensing Imagery Using Neural Networks
PublikacjaThe effective detection of objects in remote sensing images is of great research importance, so recent years have seen a significant progress in deep learning techniques in this field. However, despite much valuable research being conducted, many challenges still remain. A lot of research projects focus on detecting objects of a single category (class), while correctly detecting objects of different categories is much harder. The...
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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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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...
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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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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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Vehicle detector training with labels derived from background subtraction algorithms in video surveillance
PublikacjaVehicle detection in video from a miniature station- ary closed-circuit television (CCTV) camera is discussed in the paper. The camera provides one of components of the intelligent road sign developed in the project concerning the traffic control with the use of autonomous devices being developed. Modern Convolutional Neural Network (CNN) based detectors need big data input, usually demanding their manual labeling. In the presented...
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A Study of Cross-Linguistic Speech Emotion Recognition Based on 2D Feature Spaces
PublikacjaIn this research, a study of cross-linguistic speech emotion recognition is performed. For this purpose, emotional data of different languages (English, Lithuanian, German, Spanish, Serbian, and Polish) are collected, resulting in a cross-linguistic speech emotion dataset with the size of more than 10.000 emotional utterances. Despite the bi-modal character of the databases gathered, our focus is on the acoustic representation...
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Ranking Speech Features for Their Usage in Singing Emotion Classification
PublikacjaThis paper aims to retrieve speech descriptors that may be useful for the classification of emotions in singing. For this purpose, Mel Frequency Cepstral Coefficients (MFCC) and selected Low-Level MPEG 7 descriptors were calculated based on the RAVDESS dataset. The database contains recordings of emotional speech and singing of professional actors presenting six different emotions. Employing the algorithm of Feature Selection based...
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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...
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Impact of SDN Controller’s Performance on Quality of Service
PublikacjaSoftware Defined Networking is a paradigm in network architecture; that is quickly becoming commonplace in modern telecommunication systems. It facilitates network customization for the requirements of different applications and simplifies the implementation of new services. Since its proposal, a significant evolution in its functionality has occurred. However, this development brought along problems of efficiency and performance,...
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Information System for Drivers Within the Integrated Traffic Management System - TRISTAR
PublikacjaAdvanced traveler information systems (ATIS) for drivers are a very important element of modern traffic management. In recent years ITS infrastructure is being developed also in Poland. It allows for delivering to drivers information related to the conditions in the road network through, inter alia, dedicated Variable Message Signs (VMS). Such information enables drivers to take decisions, contributing to improving the efficiency...