Wyniki wyszukiwania dla: NEURAL NETWORK ARCHITECTURE SEARCH
-
Video of LEGO bricks on conveyor belt - wheels, tires and caterpillars
Dane BadawczeThe set contains videos of LEGO bricks (wheels, tires and caterpillars) moving on a white conveyor belt. The images were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary camera located...
-
Extensions of ETSI performance measurements methodology for statistical results analysis =Rozszerzenia metodologii pomiarów wydajności zaproponowanej przez ETSI przy statystycznej analizy wyników
PublikacjaNext Generation Network (NGN) architecture was proposed by International Telecommunication Union Telecommunication Standardization Sector (ITU-T) to deliver telecommunication services satisfying the needs of modern society for an access to information. The core of NGN service stratum are IP Multimedia Subsystem (IMS) elements acting as service controls units. To assess performance of IMS components, European Telecommunications...
-
A survey of strategies for communication networks to protect against large-scale natural disasters
PublikacjaRecent natural disasters have revealed that emergency networks presently cannot disseminate the necessary disaster information, making it difficult to deploy and coordinate relief operations. These disasters have reinforced the knowledge that telecommunication networks constitute a critical infrastructure of our society, and the urgency in establishing protection mechanisms against disaster-based disruptions. Hence, it is important...
-
A sense of security and freedom in a residential environment
PublikacjaThe article is based on the results of a survey carried out among students of architecture faculties in several countries, which examined the students’ knowledge of shaping the housing environment in such a way as to enable them to fulfil two basic and, at the same time, seemingly mutually exclusive psychological needs of a person: a sense of security and a sense of freedom. In examining these issues, particular emphasis was placed...
-
Style Transfer for Detecting Vehicles with Thermal Camera
PublikacjaIn this work we focus on nighttime vehicle detection for intelligent traffic monitoring from the thermal camera. To train a Convolutional Neural Network (CNN) detector we create a stylized version of COCO (Common Objects in Context) dataset using Style Transfer technique that imitates images obtained from thermal cameras. This new dataset is further used for fine-tuning of the model and as a result detection accuracy on images...
-
Dekodowanie kodów iterowanych z użyciem sieci neuronowej
PublikacjaNadmiarowe kody iterowane są jedną z prostych metod pozyskiwania długich kodów korekcyjnych zapewniających dużą ochronę przed błędami. Jednocześnie, chociaż ich podstawowy iteracyjny dekoder jest prosty koncepcyjnie oraz łatwy w implementacji, to nie jest on rozwiązaniem optymalnym. Poszukując alternatywnych rozwiązań zaproponowano, przedstawioną w pracy, strukturę dekodera tego typu kodów wspomaganą przez sieci neuronowe. Zaproponowane...
-
Mechanizmy bezpieczeństwa transmisji w systemie netBaltic
Publikacjaartykule zaprezentowano założenia dotyczące zabezpieczania węzłów sieci realizowanej w ramach systemu netBaltic. Ze względu na dużą różnorodność rozważanych mechanizmów komunikacyjnych architektura bezpieczeństwa została podzielona na kilka elementów – infrastrukturę klucza publicznego (PKI), bezpieczeństwo systemowe węzłów, zabezpieczanie komunikacji w modelu samoorganizującej wieloskokowej sieci kratowej, a także sieci niewrażliwej...
-
Inteligentne systemy agentowe w systemach zdalnego nauczania
PublikacjaW pracy omówiono inteligentne systemy agentowe w systemach zdalnego nauczania. Po krótkim przedstawieniu ewolucji systemów zdalnego nauczania i ich wybranych zastosowań, scharakteryzowano inteligentne agenty edukacyjne. Omówiono wykorzystanie programowania genetycznego oraz algorytmów neuro-ewolucyjnych do implementacji oprogramowania tej klasy. Ponadto, nawiązano do modelu Map-Reduce, który efektywnie wspiera architekturę nowoczesnego...
-
Residual MobileNets
PublikacjaAs modern convolutional neural networks become increasingly deeper, they also become slower and require high computational resources beyond the capabilities of many mobile and embedded platforms. To address this challenge, much of the recent research has focused on reducing the model size and computational complexity. In this paper, we propose a novel residual depth-separable convolution block, which is an improvement of the basic...
-
Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublikacjaThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
-
DATABASE AND BIGDATA PROCESSING SYSTEM FOR ANALYSIS OF AIS MESSAGES IN THE NETBALTIC RESEARCH PROJECT
PublikacjaA specialized database and a software tool for graphical and numerical presentation of maritime measurement results has been designed and implemented as part of the research conducted under the netBaltic project (Internet over the Baltic Sea – the implementation of a multi-system, self-organizing broadband communications network over the sea for enhancing navigation safety through the development of e-navigation services.) The...
-
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...
-
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...
-
Zastosowanie sieci neuronowych do detekcji impulsów o znanym kształcie w obecności silnego szumu i trendu
PublikacjaDetekcja impulsów w odebranym sygnale radiowym, zwłaszcza w obecności silnego szumu oraz trendu, jest trudnym zadaniem. Artykuł przedstawia propozycje rozwiązań wykorzystujących sieci neuronowe do detekcji impulsów o znanym kształcie w obecności silnego szumu i trendu. Na potrzeby realizacji tego zadania zaproponowano dwie architektury. W pracy przedstawiono wyniki badań wpływu kształtu impulsu, mocy zakłóceń szumowych oraz trendu...
-
Architektura bezpieczeństwa systemu netBaltic
PublikacjaW artykule zaprezentowano założenia dotyczące zabezpieczania węzłów sieci realizowanej w ramach systemu netBaltic. Ze względu na dużą różnorodność rozważanych mechanizmów komunikacyjnych architektura bezpieczeństwa została podzielona na kilka elementów – infrastrukturę klucza publicznego (PKI), bezpieczeństwo systemowe węzłów, zabezpieczanie komunikacji w modelu samoorganizującej wieloskokowej sieci kratowej, a także sieci niewrażliwej...
-
Physics-guided neural networks (PGNNs) to solve differential equations for spatial analysis
PublikacjaNumerous examples of physically unjustified neural networks, despite satisfactory performance, generate contradictions with logic and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage involves extending...
-
JAKOŚĆ USŁUG W ARCHITEKTURZE SIECI ASON/GMPLS A MECHANIZMY REZERWACJI ZASOBÓW
PublikacjaW artykule przedstawiono mechanizmy rezerwacji zasobów w architekturze sieci ASON/GMPLS, która spełnia wymagania nowoczesnych sieci optycznych, a jednocześnie umożliwia sterowanie siecią z gwarancją jakości usług. W artykule porównano dwa mechanizmy rezerwacji zasobów z gwarancją jakości i podejściem typu POOL. Efektywność prezentowanych mechanizmów zweryfikowano metodą symulacji komputerowej w środowisku OMNeT++.
-
Deep learning approach on surface EEG based Brain Computer Interface
PublikacjaIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
-
Approximation of Fractional Order Dynamic Systems Using Elman, GRU and LSTM Neural Networks
PublikacjaIn the paper, authors explore the possibility of using the recurrent neural networks (RNN) - Elman, GRU and LSTM - for an approximation of the solution of the fractional-orders differential equations. The RNN network parameters are estimated via optimisation with the second order L-BFGS algorithm. It is done based on data from four systems: simple first and second fractional order LTI systems, a system of fractional-order point...
-
Call Control Evaluation in ASON/GMPLS Architecture
PublikacjaThe Automatically Switched Optical Network (ASON) utilizing Generalized Multi–Protocol Label Switching (GMPLS) protocols named as ASON/GMPLS is one of the propositions of Next Generation Network. The basic assumption of ASON control plane is a separation of call control from connection control. The control plane is divided into call control and connection control components. Presented work regards the problem of call control evaluation...
-
A heterogenous wireless system for maritime communication - the netBaltic system architecture
PublikacjaIn the article, the concept of a heterogeneous wireless maritime mesh network offering transmission for e.g., e-navigation services is presented. The constrains of existing and competitive solutions are discussed showing the need for a new system. The authors present detailed information about a netBaltic node's architecture and networking mechanisms offering different transmission capabilities and proposed for use on different...
-
Radio system for monitoring and acquisition of data from traffic enforcement cameras - features and assumptions of the system
PublikacjaThe study presents the architecture and selected functional assumptions of Radio System for Monitoring and Acquisition of Data from Traffic Enforcement Cameras (RSMAD). Ultimately, the system will be used for transmission and archiving image data of traffic offenses, but can also perform other duties related to traffic safety. Implementation of the RSMAD system will facilitate, inter alia, issuing the fine process and supervision...
-
Low-Cost Quasi-Global Optimization of Expensive Electromagnetic Simulation Models by Inverse Surrogates and Response Features
PublikacjaConceptual design of contemporary high-frequency structures is typically followed by a careful tuning of their parameters, predominantly the geometry ones. The process aims at improving the relevant performance figures, and may be quite expensive. The reason is that conventional design methods, e.g., based on analytical or equivalent network models, often only yield rough initial designs. This is especially the case for miniaturized...
-
Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening
PublikacjaBeta-glucosidase inhibitors play important medical and biological roles. In this study, simple two-variable artificial neural network (ANN) classification models were developed for beta-glucosidase inhibitors screening. All bioassay data were obtained from the ChEMBL database. The classifiers were generated using 2D molecular descriptors and the data miner tool available in the STATISTICA package (STATISTICA Automated Neural...
-
An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublikacjaIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
-
Theory vs. practice. Searching for a path of practical education
PublikacjaThe introduction of a three-tier model of higher education (the Bologna model) has led to considerable changes in the 1st- and 2nd-tier technical courses at universities. At present, a student with a bachelor’s degree can be employed in his / her profession after completing only 7 semesters of study. A search is under way for methods of combining theoretical knowledge taught at universities with practical knowledge gained afterwards....
-
Hanna Obracht-Prondzyńska dr inż. arch.
OsobyDr inż. arch. Hanna Obracht-Prondzyńska Adiunktka na Uniwersytecie Gdańskim w Zakładzie Gospodarki Przestrzennej, nauczycielka akademicka ucząca projektowania urbanistycznego i analizy danych. Architektka i urbanistka zajmującą się projektowaniem w oparciu o dane. Tytuł doktora nauk inżynieryjno-technicznych w dyscyplinie architektura i urbanistyka obroniła z wyróżnieniem w 2020 r. na Wydziale Architektury Politechniki Gdańskiej,...
-
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...
-
Intelligent Autonomous Robot Supporting Small Pets in Domestic Environment
PublikacjaIn this contribution, we present preliminary results of the student project aimed at the development of an intelligent autonomous robot supporting small pets in a domestic environment. The main task of this robot is to protect a freely moving small pets against accidental stepping on them by home residents. For this purpose, we have developed the mobile robot which follows a pet and makes an alarm signal when a human is approaching....
-
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...
-
Architektury klasyfikatorów obrazów
PublikacjaKlasyfikacja obrazów jest zagadnieniem z dziedziny widzenia komputerowego. Polega na całościowej analizie obrazu i przypisaniu go do jednej lub wielu kategorii (klas). Współczesne rozwiązania tego problemu są w znacznej części realizowane z wykorzystaniem konwolucyjnych głębokich sieci neuronowych (convolutional neural network, CNN). W tym rozdziale opisano przełomowe architektury CNN oraz ewolucję state-of-the-art w klasyfikacji...
-
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...
-
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...
-
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...
-
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:...
-
Bridging theory and practice in postgraduate education on development and planning: Gdynia Urban Summer Schools 2016-2018
PublikacjaIn this article, the authors discuss results achieved by the Gdynia Urban Summer School (GUSS) organised annually (between 2016 and 2018) in Gdynia, Poland. The GUSS was meant for young practitioners from various professions such as urban and regional planning, urban design, architecture, civil engineering and transport planning. The objective was to give workshop participantspractical interdisciplinary...
-
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...
-
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...
-
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,...
-
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...
-
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...
-
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,...
-
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...
-
Deep Features Class Activation Map for Thermal Face Detection and Tracking
PublikacjaRecently, capabilities of many computer vision tasks have significantly improved due to advances in Convolutional Neural Networks. In our research, we demonstrate that it can be also used for face detection from low resolution thermal images, acquired with a portable camera. The physical size of the camera used in our research allows for embedding it in a wearable device or indoor remote monitoring solution for elderly and disabled...
-
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...
-
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...
-
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...
-
Machine Learning and Deep Learning Methods for Fast and Accurate Assessment of Transthoracic Echocardiogram Image Quality
PublikacjaHigh-quality echocardiogram images are the cornerstone of accurate and reliable measurements of the heart. Therefore, this study aimed to develop, validate and compare machine learning and deep learning algorithms for accurate and automated assessment of transthoracic echocardiogram image quality. In total, 4090 single-frame two-dimensional transthoracic echocardiogram...
-
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:...
-
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...