Filtry
wszystkich: 2308
wybranych: 1760
-
Katalog
- Publikacje 1760 wyników po odfiltrowaniu
- Czasopisma 112 wyników po odfiltrowaniu
- Konferencje 109 wyników po odfiltrowaniu
- Osoby 97 wyników po odfiltrowaniu
- Projekty 5 wyników po odfiltrowaniu
- Kursy Online 38 wyników po odfiltrowaniu
- Wydarzenia 4 wyników po odfiltrowaniu
- Dane Badawcze 183 wyników po odfiltrowaniu
Filtry wybranego katalogu
wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: Artificial neural networks
-
A new analyzer based on pellistor sensor with neural network data postprocessing for measurement of hydrocarbons in lower explosive limit range
PublikacjaW pracy przedstawiono rezultaty pierwszego etapu badań nad nowym typem analizatora do oznaczania stężenia wodoru i lotnych węglowodorów w zakresie dolnej granicy wybuchowości. Analizator ten zbudowano w oparciu o pojedynczy czujnik pelistorowy z układem przetwarzania danych wykorzystującym sztuczną sieć neuronową.
-
CNN Architectures for Human Pose Estimation from a Very Low Resolution Depth Image
PublikacjaThe paper is dedicated to proposing and evaluating a number of convolutional neural network architectures for calculating a multiple regression on 3D coordinates of human body joints tracked in a single low resolution depth image. The main challenge was to obtain a high precision in case of a noisy and coarse scan of the body, as observed by a depth sensor from a large distance. The regression network was expected to reason about...
-
Fast service restoration under shared protection at lightpath level in survivable WDM mesh grooming networks
PublikacjaW artykule zaproponowano nowe podejście do optymalizacji rozdziału zasobów w przeżywalnych sieciach optycznych z agregacją strumieni ruchu. Zaproponowana metoda bazuje na wierzchołkowym kolorowaniu grafu konfliktów. Jest pierwszym podejściem, dedykowanym sieciom optycznym z agregację strumieni ruchu z pełną zdolnością do konwersji długości fal, która nie powoduje wydłużenia ściezek zabezpieczjących, a więc zapewnia szybkie odtwarzanie...
-
Probability estimation of the city’s energy efficiency improvement as a result of using the phase change materials in heating networks
Publikacja -
Selfishness Detection in Mobile Ad Hoc Networks: How Dissemination of Indirect Information Turns into Strategic Issue
PublikacjaDla środowiska sieci mobilnej ad hoc przedyskutowano wymienność pomiędzy wydatkiem energetycznym węzła egoistycznego a obniżaniem jego metryki reputacyjnej. Badania symulacyjne wskazują, że atakom polegającym na selektywnym usuwaniu pakietów można przeciwdziałać poprzez datacentryczny system reputacyjny bazujący na potwierdzeniach końcowych, który nakazuje jednakowo uaktualniać metryki reputacyjne dla wszystkich węzłów na źle zachowującej...
-
Multicast Traffic Throughput Maximization through Dynamic Modulation and Coding Scheme Assignment in Wireless Sensor Networks
Publikacja -
Towards the 4th industrial revolution: networks, virtuality, experience based collective computational intelligence, and deep learning
PublikacjaQuo vadis, Intelligent Enterprise? Where are you going? The authors of this paper aim at providing some answers to this fascinating question addressing emerging challenges related to the concept of semantically enhanced knowledge-based cyber-physical systems – the fourth industrial revolution named Industry 4.0.
-
Open-Set Speaker Identification Using Closed-Set Pretrained Embeddings
PublikacjaThe paper proposes an approach for extending deep neural networks-based solutions to closed-set speaker identification toward the open-set problem. The idea is built on the characteristics of deep neural networks trained for the classification tasks, where there is a layer consisting of a set of deep features extracted from the analyzed inputs. By extracting this vector and performing anomaly detection against the set of known...
-
Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches
Publikacja -
Application of Generalized Regression Neural Network and Gaussian Process Regression for Modelling Hybrid Micro-Electric Discharge Machining: A Comparative Study
Publikacja -
ADAPTIVE PREDICTIONS OF THE EURO/ZŁOTY CURRENCY EXCHANGE RATE USING STATE SPACE WAVELET NETWORKS AND FORECAST COMBINATIONS
PublikacjaThe paper considers the forecasting of the euro/Polish złoty (EUR/PLN) spot exchange rate by applying state space wavelet network and econometric forecast combination models. Both prediction methods are applied to produce one-trading-day- ahead forecasts of the EUR/PLN exchange rate. The paper presents the general state space wavelet network and forecast combination models as well as their underlying principles. The state space...
-
A new fuzzy model of multi-criteria decision support based on Bayesian networks for the urban areas' decarbonization planning
Publikacja -
A new approach to inter-layer sharing providing differentiated protection services in survivable IP-MPLS/WDM networks
PublikacjaArtykuł omawia zagadnienie ochrony transmisji o charakterze połączeniowym w sieciach wielowarstwowych IP-MPLS/WDM. W szczególności prezentuje nową metodę współdzielenia międzywarstwowego zasobów ścieżek zabezpieczających gwarantującą szybkie odtwarzanie uszkodzonych połączeń (nawet o 40% szybciej w porównaniu z powszechnie stosowaną metodą).
-
Knowledge management in the IPv6 migration process
PublikacjaThere are many reasons to deploy IPv6 protocol with IPv4 address space depletion being the most obvious. Unfortunately, migration to IPv6 protocol seems slower than anticipated. To improve pace of the IPv6 deployment, authors of the article developed an application that supports the migration process. Its main purpose is to help less experienced network administrators to facilitate the migration process with a particular target...
-
Using Deep Neural Network Methods for Forecasting Energy Productivity Based on Comparison of Simulation and DNN Results for Central Poland—Swietokrzyskie Voivodeship
Publikacja -
Using Deep Neural Network Methods for Forecasting Energy Productivity Based on Comparison of Simulation and DNN Results for Central Poland – Swietokrzyskie Voivodeship
Publikacja -
Data augmentation for improving deep learning in image classification problem
PublikacjaThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
-
Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublikacjaThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
-
Application of Bayesian networks for inferring cause–effect relations from gene expression profiles of cancer versus normal cells
Publikacja -
Fiber optic interface channels for united data and power supply transmission for neutral interaction application in signal transmission networks
Publikacja -
Thermal analysis and experimental verification of permanent magnet synchronous motor by combining lumped-parameter thermal networks with analytical method
Publikacja -
Dispersive Delay Structures With Asymmetric Arbitrary Group-Delay Response Using Coupled-Resonator Networks With Frequency-Variant Couplings
PublikacjaThis article reports the design of coupled-resonatorbased microwave dispersive delay structures (DDSs) with arbitrary asymmetric-type group delay response. The design process exploits a coupling matrix representation of the DDS circuit as a network of resonators with frequency-variant couplings (FVCs). The group delay response is shaped using complex transmission zeros (TZs) created by dispersive cross-couplings. We also present an...
-
Rating by detection: an artifact detection protocol for rating EEG quality with average event duration
PublikacjaQuantitative evaluation protocols are critical for the development of algorithms that remove artifacts from real EEG optimally. However, visually inspecting the real EEG to select the top-performing artifact removal pipeline is infeasible while hand-crafted EEG data allow assessing artifact removal configurations only in a simulated environment. This study proposes a novel, principled approach for quantitatively evaluating algorithmically...
-
Aquaponics Based Artificial Biosphere Included in Architecture: From Mitigation of Negative Impacts to Positive Added Values of Urban Spatial Structures on Local, Regional and Global Scale
PublikacjaTechnologies may appear faster than spatial planning can afford it. Alt hough applying new technologies solve particular problems, it may also create new ones. Many negative consequences of implementing new technologies are visible a fter years or decades – they accumulate until the need of solving them. According to The Hannover Principles (McDonough & Braungart 2013) one should, by example not think about...
-
Determination of eight artificial sweeteners and common Stevia rebaudiana glycosides in non-alcoholic and alcoholic beverages by reversed-phase liquid chromatography coupled with tandem mass spectrometry.
PublikacjaThe method for the determination of acesulfame-K, saccharine, cyclamate, aspartame, sucralose, alitame, neohesperidin dihydrochalcone, neotame and five common steviol glycosides (rebaudioside A, rebaudioside C, steviol, steviolbioside and stevioside) in soft and alcoholic beverages was developed using high-performance liquid chromatography and tandem mass spectrometry with electrospray ionisation (HPLC-ESI-MS/MS). To the best of...
-
Neurocontrolled Car Speed System
PublikacjaThe features of the synthesis of neural controllers for the car speed control system are considered in this article. The task of synthesis is to determine the weight coefficients of neural networks that provide the implementation of proportional and proportional-integralderivative control laws. The synthesis of controllers is based on an approach that uses a reversed model of the standard. A model of the car speed control system with...
-
Breast MRI segmentation by deep learning: key gaps and challenges
PublikacjaBreast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...
-
Optymalizacja zasad koegzystencji sieci standardów Bluetooth i IEEE 802.11 = Optimization of Bluetooth and IEEE 802.11 networks co-existence
PublikacjaZ uwagi na rosnącą popularność standardów Bluetooth (BT) i IEEE 802.11b (Wi-Fi ) można się z nimi spotkać praktycznie wszędzie. Gwałtowny wzrost liczby urządzeń różnych technologii ma także swoje negatywne strony. Stosowanie coraz większej liczby urządzeń różnych systemów radiokomunikacyjnych powoduje wzrost poziomu zaburzeń elektromagnetycznych. W konsekwencji działanie różnych sieci bezprzewodowych pracujących w bliskim zasięgu...
-
Corrosion behaviour of low carbon steel in artificial seawater using TP, LP, EIS, Harmonic Analysis (HA) and new method Dynamic Electrochemical Impedance Spectroscopy (DEIS)
PublikacjaZe względu na istotną rolę technik elektrochemicznych w badaniach procesów korozyjnych są one szeroko stosowane w monitorowaniu korozji. Celem niniejszej pracy jest zgromadzenie rezultatów wyników doświadczalnych uzyskanych różnymi technikami i znalezienie korelacji między nimi. Własności korozyjne stali stopowej (AISI 1026) w sztucznej wodzie morskiej zostały zbadane z wykorzystaniem ekstrapolacji tafelowskiej (TP), polaryzacji...
-
Zastosowanie algorytmu ewolucyjnego do uczenia neuronowego regulatora napięcia generatora synchronicznego. Evolutionary algorithm for training a neural network of synchronous generator voltage controller
PublikacjaNajpopularniejsza metoda uczenia wielowarstwowych sieci neuronowych -metoda wstecznej propagacji błędu - charakteryzuje się słabą efektywnością. Z tego względu podejmowane są próby stosowania innych metod do uczenia sieci. W pracy przedstawiono wyniki uczenia sieci realizującej regulator neuronowy, za pomocą algorytmu ewolucyjnego. Obliczenia symulacyjne potwierdziły dobrą zbieżność algorytmu ewolucyjnego w tym zastosowaniu.
-
Multicast Traffic Throughput Maximization through Joint Dynamic Modulation and Coding Schemes Assignment, and Transmission Power Control in Wireless Sensor Networks
Publikacja -
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...
-
Experience-Based Cognition for Driving Behavioral Fingerprint Extraction
PublikacjaABSTRACT With the rapid progress of information technologies, cars have been made increasingly intelligent. This allows cars to act as cognitive agents, i.e., to acquire knowledge and understanding of the driving habits and behavioral characteristics of drivers (i.e., driving behavioral fingerprint) through experience. Such knowledge can be then reused to facilitate the interaction between a car and its driver, and to develop better and...
-
Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublikacjaSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
-
Cognitive motivations and foundations for building intelligent decision-making systems
PublikacjaConcepts based on psychology fit well with current research trends related to robotics and artificial intelligence. Biology-inspired cognitive architectures are extremely useful in building agents and robots, and this is one of the most important challenges of modern science. Therefore, the widely viewed and far-reaching goal of systems research and engineering is virtual agents and autonomous robots that mimic human behavior in...
-
Widespread theta synchrony and high-frequency desynchronization underlies enhanced cognition
PublikacjaThe idea that synchronous neural activity underlies cognition has driven an extensive body of research in human and animal neuroscience. Yet, insufficient data on intracranial electrical connectivity has precluded a direct test of this hypothesis in a whole-brain setting. Through the lens of memory encoding and retrieval processes, we construct whole-brain connectivity maps of fast gamma (30-100 Hz) and slow theta (3-8 Hz) spectral...
-
A Novel IoT-Perceptive Human Activity Recognition (HAR) Approach Using Multi-Head Convolutional Attention
PublikacjaTogether with fast advancement of the Internet of Things (IoT), smart healthcare applications and systems are equipped with increasingly more wearable sensors and mobile devices. These sensors are used not only to collect data, but also, and more importantly, to assist in daily activity tracking and analyzing of their users. Various human activity recognition (HAR) approaches are used to enhance such tracking. Most of the existing...
-
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,...
-
Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublikacjaThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
-
Classifying Emotions in Film Music - A Deep Learning Approach
PublikacjaThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
-
Data regarding a new, vector-enzymatic DNA fragment amplification-expression technology for the construction of artificial, concatemeric DNA, RNA and proteins, as well as biological effects of selected polypeptides obtained using this method
PublikacjaApplications of bioactive peptides and polypeptides are emerging in areas such as drug development and drug delivery systems. These compounds are bioactive, biocompatible and represent a wide range of chemical properties, enabling further adjustments of obtained biomaterials. However, delivering large quantities of peptide derivatives is still challenging. Several methods have been developed for the production of concatemers –...
-
Speech Analytics Based on Machine Learning
PublikacjaIn this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...
-
Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
-
Document Agents with the Intelligent Negotiations Capability
PublikacjaThe paper focus is on augmenting proactive document-agents with built -in intelligence to enable them to recognize execution context provided by devices visited durning the business process, and to reach collaboration agreement despite of their conflicting requirements. We propose a solution based on neural networks to improve simple multi-issue negotiation between the document and the device, practically with no excessive cost...
-
Neuronowa symulacja temperatury i ciśnienia pary w upuście parowego bloku energetycznego = Neural simulation of pressure and temperature fluctuations at steam extraction of power units with steam turbine
PublikacjaW artykule przedstawiono metodę symulacji neuronowej dla zastosowań w diagnostyce on-line bloków energetycznych. Model neuronowy opiera się na statycznych jednokierunkowych sieciach neuronowych (SSN) oraz na danych z parowego bloku energetycznego o mocy 200 MW. SSN obliczają wartości referencyjne parametrów cieplno-przepływowych dla aktualnego obciążenia obiektu. Określono wpływ architektury sieci i danych uczących na jakość symulacji...
-
Zarządzanie (współzarządzanie) sieciowe i zarządzanie sieciami w wymiarze sprawiedliwości – wyzwania (15 stron) Governance network and networks governance in the justice system – challenges
PublikacjaCelem artykułu jest próba odpowiedzi na pytania czy w wymiarze sprawiedliwości jest miejsce i podstawa do wdrożenia zarządzania sieciowego (współzarządzania) oraz czy w działalności pomocniczej wymiaru sprawiedliwości istnieje potencjał do jego wdrożenia. W wymiarze sprawiedliwości istnieje duży potencjał do wykorzystania mechanizmów sieciowej współpracy. W ramach przestrzeni wymiaru sprawiedliwości współpraca międzyorganizacyjna...
-
Towards Knowledge Sharing Oriented Adaptive Control
PublikacjaIn this paper, we propose a knowledge sharing oriented approach to enable a robot to reuse other robots' knowledge by adapting itself to the inverse dynamics model of the knowledge-sharing robot. The purpose of this work is to remove the heavy fine-tuning procedure required before using a new robot for a task via reusing other robots' knowledge. We use the Neural Knowledge DNA (NK-DNA) to help robots gain empirical knowledge and...
-
Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublikacjaCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
-
Selection of Features for Multimodal Vocalic Segments Classification
PublikacjaEnglish speech recognition experiments are presented employing both: audio signal and Facial Motion Capture (FMC) recordings. The principal aim of the study was to evaluate the influence of feature vector dimension reduction for the accuracy of vocalic segments classification employing neural networks. Several parameter reduction strategies were adopted, namely: Extremely Randomized Trees, Principal Component Analysis and Recursive...
-
BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublikacjaIn 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...