Wyniki wyszukiwania dla: CONVOLUTIONAL NEUTRAL NETWORKS - MOST Wiedzy

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Wyniki wyszukiwania dla: CONVOLUTIONAL NEUTRAL NETWORKS

Wyniki wyszukiwania dla: CONVOLUTIONAL NEUTRAL NETWORKS

  • Performance Analysis of Convolutional Neural Networks on Embedded Systems

    Publikacja

    - Rok 2020

    Machine learning is no longer confined to cloud and high-end server systems and has been successfully deployed on devices that are part of Internet of Things. This paper presents the analysis of performance of convolutional neural networks deployed on an ARM microcontroller. Inference time is measured for different core frequencies, with and without DSP instructions and disabled access to cache. Networks use both real-valued and...

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  • Clothes Detection and Classification Using Convolutional Neural Networks

    Publikacja

    In this paper we describe development of a computer vision system for accurate detection and classification of clothes for e-commerce images. We present a set of experiments on well established architectures of convolutional neural networks, including Residual networks, SqueezeNet and Single Shot MultiBox Detector (SSD). The clothes detection network was trained and tested on DeepFashion dataset, which contains box annotations...

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  • Architectural Modifications to Enhance Steganalysis with Convolutional Neural Networks

    Publikacja

    This paper investigates the impact of various modifications introduced to current state-of-the-art Convolutional Neural Network (CNN) architectures specifically designed for the steganalysis of digital images. Usage of deep learning methods has consistently demonstrated improved results in this field over the past few years, primarily due to the development of newer architectures with higher classification accuracy compared to...

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  • Characterizing the Scalability of Graph Convolutional Networks on Intel® PIUMA

    Publikacja
    • M. J. Adiletta
    • J. J. Tithi
    • E. Farsarakis
    • G. Gerogiannis
    • R. Adolf
    • R. Benke
    • S. Kashyap
    • S. Hsia
    • K. Lakhotia
    • F. Petrini... i 2 innych

    - Rok 2023

    Large-scale Graph Convolutional Network (GCN) inference on traditional CPU/GPU systems is challenging due to a large memory footprint, sparse computational patterns, and irregular memory accesses with poor locality. Intel’s Programmable Integrated Unffied Memory Architecture (PIUMA) is designed to address these challenges for graph analytics. In this paper, a detailed characterization of GCNs is presented using the Open-Graph Benchmark...

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  • Extraction of music information based on artifical neutral networks

    Publikacja

    - Rok 2003

    W artykule przedstawiono założenia systemu automatycznego rozpoznawania muzyki. Na podstawie przeprowadzonych eksperymentów w artykule przedstawiono efektywność zaimplementowanych algorytmów w zależności od sposobu opisu danych muzycznych. Zaimpementowany system jest oparty o sztuczne sieci neuronowe.

  • Automatic Breath Analysis System Using Convolutional Neural Networks

    Publikacja

    Diseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is common for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected as...

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  • Automatic Breath Analysis System Using Convolutional Neural Networks

    Publikacja

    Diseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is not uncommon for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected...

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  • Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets

    Artificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...

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  • System for monitoring road slippery based on CCTV cameras and convolutional neural networks

    Publikacja

    The slipperiness of the surface is essential for road safety. The growing number of CCTV cameras opens the possibility of using them to automatically detect the slippery surface and inform road users about it. This paper presents a system of developed intelligent road signs, including a detector based on convolutional neural networks (CNNs) and the transferlearning method employed to the processing of images acquired with video...

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  • A Novel Iterative Decoding for Iterated Codes Using Classical and Convolutional Neural Networks

    Publikacja

    - Rok 2024

    Forward error correction is crucial for communication, enabling error rate or required SNR reduction. Longer codes improve correction ratio. Iterated codes offer a solution for constructing long codeswith a simple coder and decoder. However, a basic iterative code decoder cannot fully exploit the code’s potential, as some error patterns within its correction capacity remain uncorrected.We propose two neural network-assisted decoders:...

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  • Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks

    Publikacja

    The presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods....

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  • Intelligent acquisition of audio signals, employing neutral networks and rough set algorithms

    Publikacja

    - Rok 2003

    Algorytmy oparte na sztucznych sieciach neuronowych i metodzie zbiorówprzybliżonych zostały zastosowane do lokalizacji sygnałów fonicznych obar-czonych pasożytniczym szumem i rewerberacjami. Informacja o kierunku napły-wania dźwięku była uzyskiwana na wyjściach tych algorytmów na podstawie re-prezentacji parametrycznej. Przedstawiono wyniki eksperymentalne i przepro-wadzono ich dyskusję.

  • Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening

    Publikacja

    Familial 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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  • A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification

    The article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...

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  • Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features

    Nematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...

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  • DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY

    The paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...

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  • Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks

    Publikacja
    • T. Dziubich
    • P. Białas
    • Ł. Znaniecki
    • J. Halman
    • J. Brzeziński

    - Rok 2020

    One of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...

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  • GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition

    Publikacja

    In the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...

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  • Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks

    Age prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...

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  • Fiber optic interface channels for united data and power supply transmission for neutral interaction application in signal transmission networks

    Publikacja

    - Rok 2019

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  • Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2018

    This work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...

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  • Activation maps of convolutional neural networks as a tool for brain degeneration tracking in early diagnosis of dementia in Parkinson's disease based on magnetic resonance imaging

    Publikacja
    • A. Suwalska
    • J. Siuda
    • S. Kocot
    • W. Zmuda
    • M. Rudzinska-Bar
    • J. Polanska

    - Rok 2021

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  • СИСТЕМА КОНТРОЛЯ СОСТОЯНИЯ ИЗОЛЯЦИИ ЭЛЕКТРОПРИВОДОВ В СЕТЯХ С ГЛУХОЗАЗЕМЛЕННОЙ НЕЙТРАЛЬЮ (System of insulation status monitoring for electric drives in networks with a dead-earth neutral)

    Publikacja

    - Izvestiya vysshikh uchebnykh zavedeniy. Priborostroenie - Rok 2020

    Предложен метод контроля изоляции частотно-регулируемых электроприводов в сетях с глухозаземленной нейтралью. Система контроля изоляции включается в момент остановки электропривода. Ключи инвертора коммутируются по специальному закону, и с помощью сигнала трансформатора тока, который изме- ряет ток во всех трех фазах привода одновременно, определяется ток утечки. Рассмотрена схема датчика тока утечки и приведены экспериментальные...

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  • Piotr Szczuko dr hab. inż.

    Dr hab. inż. Piotr Szczuko w 2002 roku ukończył studia na Wydziale Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej zdobywając tytuł magistra inżyniera. Tematem pracy dyplomowej było badanie zjawisk jednoczesnej percepcji obrazu cyfrowego i dźwięku dookólnego. W roku 2008 obronił rozprawę doktorską zatytułowaną "Zastosowanie reguł rozmytych w komputerowej animacji postaci", za którą otrzymał nagrodę Prezesa Rady...

  • Deep neural networks for data analysis 24/25

    Kursy Online
    • J. Cychnerski
    • K. Draszawka

    This course covers introduction to supervised machine learning, construction of basic artificial deep neural networks (DNNs) and basic training algorithms, as well as the overview of popular DNNs architectures (convolutional networks, recurrent networks, transformers). The course introduces students to popular regularization techniques for deep models. Besides theory, large part of the course is the project in which students apply...

  • Deep Learning Basics 2023/24

    Kursy Online
    • K. Draszawka

    A course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.

  • Detecting Lombard Speech Using Deep Learning Approach

    Publikacja
    • K. Kąkol
    • G. Korvel
    • G. Tamulevicius
    • B. Kostek

    - SENSORS - Rok 2023

    Robust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...

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  • Badania eksperymentalne transformatora hybrydowego jako kondycjonera napięcia w sieciach typu TN

    Publikacja

    - Przegląd Elektrotechniczny - Rok 2023

    Artykuł dotyczy układu dystrybucyjnego transformatora hybrydowego (DTH) przeznaczonego do zastosowania w sieciach typu TN. Opisano w nim sposoby podłączenia przewodu neutralnego do układu DTH. W dalszej części artykuł zawiera opis skonstruowanego modelu laboratoryjnego o mocy 16 kVA wraz z zastosowanym algorytmem sterowania. Ponadto przedstawiono wyniki badań eksperymentalnych, ze szczególnym uwzględnieniem oceny dokładności stabilizacji...

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  • WYKORZYSTANIE SIECI NEURONOWYCH DO SYNTEZY MOWY WYRAŻAJĄCEJ EMOCJE

    Publikacja

    W niniejszym artykule przedstawiono analizę rozwiązań do rozpoznawania emocji opartych na mowie i możliwości ich wykorzystania w syntezie mowy z emocjami, wykorzystując do tego celu sieci neuronowe. Przedstawiono aktualne rozwiązania dotyczące rozpoznawania emocji w mowie i metod syntezy mowy za pomocą sieci neuronowych. Obecnie obserwuje się znaczny wzrost zainteresowania i wykorzystania uczenia głębokiego w aplikacjach związanych...

  • Sławomir Jerzy Ambroziak dr hab. inż.

    Sławomir J. Ambroziak urodził się w 1982 r. Uzyskał tytuł zawodowy magistra inżyniera w zakresie systemów i usług radiokomunikacyjnych w roku 2008, w 2013 r. uzyskał stopień doktora nauk technicznych w dyscyplinie telekomunikacja, w specjalności radiokomunikacja, natomiast w 2020 r. uzyskał stopień doktora habilitowanego. Od 2008 r. jest pracownikiem Katedry Systemów i Sieci Radiokomunikacyjnych na Wydziale Elektroniki, Telekomunikacji...

  • Jerzy Konorski dr hab. inż.

    Jerzy Konorski otrzymał tytuł mgr inż. telekomunikacji na Poitechnice Gdańskiej, zaś stopień doktora n.t. w dyscyplinie informatyka w Instytucie Podstaw Informatyki PAN. W r. 2007 obronił rozprawę habilitacyjną na Wydziale Elektroniki, Telekomnikacji i Informatyki PG. Jest autorem ponad 150 publikacji naukowych, prowadził projekty naukowo-badawcze finansowane ze środków Komitetu Badań Naukowych, UE, US Air Force Office of Scientific...

  • NETWORKS

    Czasopisma

    ISSN: 0028-3045 , eISSN: 1097-0037

  • An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key

    Publikacja

    - Rok 2019

    The topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...

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  • Sylwester Kaczmarek dr hab. inż.

    Sylwester Kaczmarek ukończył studia w 1972 roku jako mgr inż. Elektroniki, a doktorat i habilitację uzyskał z technik komutacyjnych i inżynierii ruchu telekomunikacyjnego w 1981 i 1994 roku na Politechnice Gdańskiej. Jego zainteresowania badawcze ukierunkowane są na: sieci IP QoS, sieci GMPLS, sieci SDN, komutację, ruting QoS, inżynierię ruchu telekomunikacyjnego, usługi multimedialne i jakość usług. Aktualnie jego badania skupiają...

  • Computer Networks-laboratories - 2023

    Kursy Online
    • M. Hoeft
    • T. Gierszewski
    • I. Szczypior
    • J. Grochowski
    • J. Rak
    • W. Gumiński
    • K. Jurczenia
    • K. Gierłowski
    • K. Nowicki

    Acquiring the skills to design, build and configure computer networks. Demonstration of skills to identify and analyze selected protocols and mechanisms of LAN and WAN networks.

  • Computer Networks laboratories 2024

    Kursy Online
    • M. Hoeft
    • T. Gierszewski
    • I. Szczypior
    • J. Grochowski
    • J. Rak
    • W. Gumiński
    • K. Jurczenia
    • K. Gierłowski
    • K. Nowicki

    Acquiring the skills to design, build and configure computer networks. Demonstration of skills to identify and analyze selected protocols and mechanisms of LAN and WAN networks.

  • Neutral point balancing technique for 3-level neutral point clamped converter with servo system

    Publikacja

    - Rok 2017

    Neutral point voltage drift compensation technique in 3-level NPC multilevel converter and servo system is described in the paper. Analytical expressions are obtained for power subsystem elements parameters of servo drive system. Simulation of servo system, based on PMSM motor with 3-level NPC converter is considered.

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  • Neutral earthing reactor protection

    The IEEE and CIGRE recommend protection systems for high voltage shunt reactors. Unfortunately the recommendations do not include guidelines for the protection of neutral earthing reactors, which are often connected to shunt reactors to increase the effectiveness of single pole auto-reclosing. The paper discusses earthing reactor protection issues with particular emphasis on the detection of internal faults. An analysis carried...

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  • From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition

    Publikacja

    Recently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...

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  • Piotr Rajchowski dr inż.

    Piotr Rajchowski (Member, IEEE) was born in Poland, in 1989. He received the E.Eng., M.Sc., and Ph.D. degrees in radio communication from the Gdańsk University of Technology (Gdańsk Tech), Poland, in 2012, 2013, and 2017, respectively. Since 2013, he has been working at the Department of Radiocommunication Systems and Networks, Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, as a IT...

  • On neutral differential equations and the monotone iterative method

    The application of the monotone iterative method to neutral differential equations with deviating arguments is considered in this paper. We formulate existence results giving sufficient conditions which guarantee that such problems have solutions. This approach is new and to the Authors' knowledge, this is the first paper when the monotone iterative method is applied to neutral first-order differential equations with deviating...

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  • Computer Networks EN 2022

    Kursy Online
    • J. Woźniak
    • J. Grochowski
    • K. Gierłowski

    The student becomes familiar with the network layered logical architectures, classifies the basic problems of network communication and identifies and analyzes selected protocols and mechanisms of LAN and WAN (IP) networks.

  • Computer Networks EN 2023

    Kursy Online
    • M. Hoeft
    • J. Woźniak
    • J. Grochowski
    • K. Gierłowski

    The student becomes familiar with the network layered logical architectures, classifies the basic problems of network communication and identifies and analyzes selected protocols and mechanisms of LAN and WAN (IP) networks.

  • A Novel IoT-Perceptive Human Activity Recognition (HAR) Approach Using Multi-Head Convolutional Attention

    Publikacja

    - IEEE Internet of Things Journal - Rok 2019

    Together 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...

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  • Modelling of wastewater treatment plant for monitoring and control purposes by state - space wavelet networks

    Publikacja

    Most of industrial processes are nonlinear, not stationary, and dynamical with at least few different time scales in their internal dynamics and hardly measured states. A biological wastewater treatment plant falls into this category. The paper considers modelling such processes for monitorning and control purposes by using State - Space Wavelet Neural Networks (SSWN). The modelling method is illustrated based on bioreactors of...

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  • Neural networks and deep learning

    Publikacja

    - Rok 2022

    In this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...

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  • Measures of region failure survivability for wireless mesh networks

    Publikacja

    - WIRELESS NETWORKS - Rok 2015

    Wireless mesh networks (WMNs) are considered as a promising alternative to wired local, or metropolitan area networks. However, owing to their exposure to various disruptive events, including natural disasters, or human threats, many WMN network elements located close to the failure epicentre are frequently in danger of a simultaneous failure, referred to as a region failure. Therefore, network survivability, being the ability...

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  • Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions

    Publikacja

    - Rok 2018

    With the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...

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  • Digits Recognition with Quadrant Photodiode and Convolutional Neural Network

    Publikacja

    - Rok 2018

    In this paper we have investigated the capabilities of a quadrant photodiode based gesture sensor in the recognition of digits drawn in the air. The sensor consisting of 4 active elements, 4 LEDs and a pinhole was considered as input interface for both discrete and continuous gestures. Index finger and a round pointer were used as navigating mediums for the sensor. Experiments performed with 5 volunteers...

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  • ThreSpect – A Program for the Determination of the Appearance Energies of Neutral and Ionized Species

    Collisions of photons and charged particles with molecules lead to their excitation, ionization, and dissociation into neutral and ionized fragments. Accurately determining thresholds of the formation of particular products plays a vital role in analyzing processes occurring during these interactions. Therefore, we present a computer program, “ThreSpect,” that allows calculating threshold energies of various species generated in...

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