Blar i Department of Electrical and Computer Engineering (TN-IDE) på emneord "nevrale nettverk"
Viser treff 1-11 av 11
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Advanced vision based vehicle classification for traffic surveillance system using neural networks
(Masteroppgave/UIS-TN-IDE/2017;, Master thesis, 2017-06)This master thesis focus on traffic monitoring, which are of importance to fulfill planning and traffic management of road networks. An important requirement is data interpretation accuracy to provide adequate characteristic ... -
Assistive Data Glove for Isolated Static Postures Recognition in American Sign Language Using Neural Network
(Peer reviewed; Journal article, 2023)Sign language recognition is one of the most challenging tasks of today’s era. Most of the researchers working in this domain have focused on different types of implementations for sign recognition. These implementations ... -
Automatic Entity Typing using Deep Learning
(Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-06-15)Knowledge bases contain vast amounts of information about entities and their semantic types. These can be leveraged in a variety of information access tasks like natural language processing and information retrieval. ... -
Bruk av nevrale nettverk for avansert deteksjon av objekter under vann.
(Masteroppgave/UIS-TN-IDE/2009;, Master thesis, 2009-06)SwimEye er et system for å øke sikkerheten mot drukningsulykker i basseng. Det er ønskelig å gjøre SwimEyes deteksjon enda bedre, og denne masteroppgaven kommer frem til en løsning på dette problemet ved bruk av et nevralt ... -
Decreasing Manual Workload by Automating SAP Travel Expense Workflows
(Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-06)In the 21st century, efficiency is a key focus for several organisations, and because of this, machine learning and process automation is getting a lot of attention. The Norwegian Government Agency of Financial Management ... -
Household Power Demand Prediction Using Evolutionary Ensemble Neural Network Pool with Multiple Network Structures
(Peer reviewed; Journal article, 2019-02)The progress of technology on energy and IoT fields has led to an increasingly complicated electric environment in low-voltage local microgrid, along with the extensions of electric vehicle, micro-generation, and local ... -
Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia
(Journal article; Peer reviewed, 2019-05)Early defibrillation by an automated external defibrillator (AED) is key for the survival of out-of-hospital cardiac arrest (OHCA) patients. ECG feature extraction and machine learning have been successfully used to detect ... -
Recurrent Neural Networks for Artifact Correction in HRV Data During Physical Exercise
(Peer reviewed; Journal article, 2023)In this paper, we propose the use of recurrent neural networks (RNNs) for artifact correction and analysis of heart rate variability (HRV) data. HRV can be a valuable metric for determining the function of the heart and ... -
Smart Meter Based Load Forecasting for Residential Customers Using Machine Learning Algorithms
(Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06-12)The focus of this thesis is the use of machine learning algorithms to perform next step short term load forecasting on fifty five households in Stavanger, Norway. A dataset containing electricity consumption data for more ... -
Synaptic Vesicle Detection in Microscopy Images using Convolutional Neural Network and Compressed Sensing
(Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-06-15)In response to stressful situations, the body activates its sympathetic nervous system with the sudden release of hormones. This increases the presence of adrenaline and noradrenaline which improves muscle strength and ... -
Testing Different Ways to analyse Data from Well Sensors Using Neural Networks and Image Processing
(Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-06-15)This thesis focuses on evaluation and testing different approaches of image recognition, neural networks and data analytics with application to the analysis of data collected from sensors installed in wells operated in the ...