Search results for: NEURONAL PROTEOSTASIS - Bridge of Knowledge

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Search results for: NEURONAL PROTEOSTASIS

Search results for: NEURONAL PROTEOSTASIS

  • Skuteczne prognozowanie krótkoterminowe mocy farm wiatrowych

    Publication

    - Acta Energetica - Year 2015

    Prognozowanie mocy wytwórczej konkretnej farmy wiatrowej (FW) w horyzoncie 24-godzinnymwymaga zarówno wiarygodnej prognozy wietrzności, jak i narzędzi wspomagających. Narzędzie to jest dedykowanym modelem mocy farmy. Model powinien uwzględniać nie tylko ogólne zasady przetwarzania energii wiatru na energię mechaniczną, ale także cechy szczególnekonkretnej farmy. Liczba czynników wpływających na moc farmy jest duża i dokładna prognozamocy,...

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  • Efficiency of Artificial Intelligence Methods for Hearing Loss Type Classification: an Evaluation

    Publication
    • M. Kassjański
    • M. Kulawiak
    • T. Przewoźny
    • D. Tretiakow
    • J. Kuryłowicz
    • A. Molisz
    • K. Koźmiński
    • A. Kwaśniewska
    • P. Mierzwińska-Dolny
    • M. Grono

    - Journal of Automation, Mobile Robotics and Intelligent Systems - JAMRIS - Year 2024

    The evaluation of hearing loss is primarily conducted by pure tone audiometry testing, which is often regarded as golden standard for assessing auditory function. If the presence of hearing loss is determined, it is possible to differentiate between three types of hearing loss: sensorineural, conductive, and mixed. This study presents a comprehensive comparison of a variety of AI classification models, performed on 4007 pure tone...

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  • Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits

    Publication

    The Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...

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  • Classifying Emotions in Film Music - A Deep Learning Approach

    The 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...

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  • Hotspot of human verbal memory encoding in the left anterior prefrontal cortex

    Publication

    - EBioMedicine - Year 2022

    Background: Treating memory and cognitive deficits requires knowledge about anatomical sites and neural activities to be targeted with particular therapies. Emerging technologies for local brain stimulation offer attractive therapeutic options but need to be applied to target specific neural activities, at distinct times, and in specific brain regions that are critical for memory formation. Methods: The areas that are critical...

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  • Data augmentation for improving deep learning in image classification problem

    Publication

    These 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...

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  • Towards Knowledge Sharing Oriented Adaptive Control

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2022

    In 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...

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  • Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"

    The 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...

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  • Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging

    Publication

    In the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...

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  • Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition

    Publication

    - JOURNAL OF THE AUDIO ENGINEERING SOCIETY - Year 2018

    convolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...

  • Optymalizacja treningu i wnioskowania sieci neuronowych

    Sieci neuronowe są jedną z najpopularniejszych i najszybciej rozwijających się dziedzin sztucznej inteligencji. Ich praktyczne wykorzystanie umożliwiło szersze użycie komputerów w wielu obszarach komunikacji, przemysłu i transportu. Dowody tego są widoczne w elektronice użytkowej, medycynie, a nawet w zastosowaniach militarnych. Wykorzystanie sztucznej inteligencji w wielu przypadkach wymaga jednak znacznej mocy obliczeniowej,...

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  • Hybrid System for Ship-Aided Design Automation

    Publication

    - Year 2011

    A hybrid support system for ship design based on the methodology of CBR with some artificial intelligence tools such as expert system Exsys Developer along with fuzzy logic, relational Access database and artificial neural network with backward propagation of errors.

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  • Breast MRI segmentation by deep learning: key gaps and challenges

    Publication

    Breast 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...

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  • Deep Learning: A Case Study for Image Recognition Using Transfer Learning

    Publication

    - Year 2021

    Deep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...

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  • Deep Learning

    Publication

    - Year 2021

    Deep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...

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  • Zdzisław Kowalczuk prof. dr hab. inż.

    Zdzislaw Kowalczuk received his M.Sc. degree in 1978 and Ph.D. degree in 1986, both in Automatic Control from Technical University of Gdańsk (TUG), Gdańsk, Poland. In 1993 he received his D.Sc. degree (Dr Habilitus) in Automatic Control from Silesian Technical University, Gliwice, Poland, and the title of Professor from the President of Poland in 2003. Since 1978 he has been with Faculty of Electronics, Telecommunications and Informatics...

  • Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment

    Atmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...

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  • Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters

    Publication

    - Year 2019

    This 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...

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  • Direct electrical brain stimulation of human memory: lessons learnt and future perspectives

    Publication

    Modulation of cognitive functions supporting human declarative memory is one of the grand challenges of neuroscience, and of vast importance for a variety of neuropsychiatric, neurodegenerative and neurodevelopmental diseases. Despite a recent surge of successful attempts at improving performance in a range of memory tasks, the optimal approaches and parameters for memory enhancement have yet to be determined. On a more fundamental...

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  • Missing Puzzle Pieces in Dementia Research: HCN Channels and Theta Oscillations

    Publication

    - Aging and Disease - Year 2024

    Increasing evidence indicates a role of hyperpolarization activated cation (HCN) channels in controlling the resting membrane potential, pacemaker activity, memory formation, sleep, and arousal. Their disfunction may be associated with the development of epilepsy and age-related memory decline. Neuronal hyperexcitability involved in epileptogenesis and EEG desynchronization occur in the course of dementia in human Alzheimer’s Disease...

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  • Language Models in Speech Recognition

    Publication

    - Year 2022

    This chapter describes language models used in speech recognition, It starts by indicating the role and the place of language models in speech recognition. Mesures used to compare language models follow. An overview of n-gram, syntactic, semantic, and neural models is given. It is accompanied by a list of popular software.

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  • Problems of modelling toxic compounds emitted by a marine internal combustion engine in unsteady states

    Publication

    Contemporary engine tests are performed based on the theory of experiment. The available versions of programmes used for analysing experimental data make frequent use of the multiple regression model, which enables examining effects and interactions between input model parameters and a single output variable. The use of multi-equation models provides more freedom in analysing the measured results, as those models enable simultaneous...

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  • Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention

    Publication

    - Year 2021

    This paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...

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  • Simulating Power Generation from Photovoltaics in the Polish Power System Based on Ground Meteorological Measurements—First Tests Based on Transmission System Operator Data

    Publication

    - ENERGIES - Year 2020

    The Polish power system is undergoing a slow process of transformation from coal to one that is renewables dominated. Although coal will remain a fundamental fuel in the coming years, the recent upsurge in installed capacity of photovoltaic (PV) systems should draw significant attention. Owning to the fact that the Polish Transmission System Operator recently published the PV hourly generation time series in this article, we aim...

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  • Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia

    Publication

    - Year 2024

    W pracy doktorskiej podjęto problem realizacji algorytmów głębokiego uczenia w warunkach deficytu danych uczących. Głównym celem było opracowanie podejścia optymalizującego strukturę sieci neuronowej oraz zastosowanie uczeniu dwuetapowym, w celu uzyskania mniejszych struktur, zachowując przy tym dokładności. Proponowane rozwiązania poddano testom na zadaniu klasyfikacji znamion skórnych na znamiona złośliwe i łagodne. W pierwszym...

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  • WYKORZYSTANIE SIECI NEURONOWYCH DO SYNTEZY MOWY WYRAŻAJĄCEJ EMOCJE

    Publication

    - Year 2018

    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...

  • Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France

    Publication
    • N. N. Navnath
    • K. Chandrasekaran
    • A. Stateczny
    • V. M. Sundaram
    • P. Panneer

    - Remote Sensing - Year 2022

    Current 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...

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  • Methods of Artificial Intelligence for Prediction and Prevention Crisis Situations in Banking Systems

    In this paper, a support vector machine has been studied due to prediction of bank crisis. To prevent outcomes of crisis situations, artificial neural networks have been characterized as applied to stock market investments, as well as to test the credibility of the bank's customers. Finally, some numerical experiments have been presented.

  • User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning

    Publication

    - SENSORS - Year 2024

    In this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...

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  • THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN

    Publication

    - Year 2021

    In the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and...

  • Potential and Use of the Googlenet Ann for the Purposes of Inland Water Ships Classification

    Publication

    - Polish Maritime Research - Year 2020

    This article presents an analysis of the possibilities of using the pre-degraded GoogLeNet artificial neural network to classify inland vessels. Inland water authorities monitor the intensity of the vessels via CCTV. Such classification seems to be an improvement in their statutory tasks. The automatic classification of the inland vessels from video recording is a one of the main objectives of the Automatic Ship Recognition and...

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  • Tagged images with LEGO bricks - Bricks Sloped

    Open Research Data
    version 1.2 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Bricks Sloped category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Tiles

    Open Research Data
    version 1.1 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Tiles category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Windscreens and Fuselage

    Open Research Data
    version 1.2 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Windscreens and Fuselage category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Bricks Special

    Open Research Data
    version 1.2 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Bricks Special category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Bricks

    Open Research Data
    version 1.3 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Bricks category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Technic Beams

    Open Research Data
    version 1.2 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Technic Beams category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Technic Pins

    Open Research Data
    version 1.2 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Technic Pins category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Minifig Accessories

    Open Research Data
    version 1.1 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Minifig Accessories category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Plates

    Open Research Data
    version 1.2 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Plates category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Technic Panels

    Open Research Data
    version 1.1 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Technic Panels category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Pneumatics

    Open Research Data
    version 1.1 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Pneumatics category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Technic Bricks

    Open Research Data
    version 1.1 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Technic Bricks category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Technic Gears

    Open Research Data
    version 1.2 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Technic Gears category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Panels

    Open Research Data
    version 1.2 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Panels category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Technic Bushes

    Open Research Data
    version 1.1 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Technic Bushes category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Transportation - Sea and Air

    Open Research Data
    version 1.1 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Transportation - Sea and Air category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Bionicle Hero Factory and Constraction

    Open Research Data
    version 1.1 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Bionicle Hero Factory and Constraction category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Tiles Round and Curved

    Open Research Data
    version 1.1 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Tiles Round and Curved category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.

  • Tagged images with LEGO bricks - Hinges Arms and Turntables

    Open Research Data
    version 1.2 open access - series: LEGO - partial

    The set contains images of LEGO bricks (from Hinges Arms and Turntables category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.