Blar i Department of Electrical and Computer Engineering (TN-IDE) på emneord "maskinlæring"

Viser treff 1-20 av 21

    • Advanced Deep Learning for Whale detection in VHR Satellite Images 

      Rabbani, Rabbir Bin (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020)
      With the use of very high resolution (VHR) satellite images we can locate whales. In this thesis, I have experimented with different advanced architectures in Deep Learning to detect whales in satellite images. I have also ...

    • Analyse og presentasjon av Mars rover data 

      Fjellheim, Markus (Masteroppgave/UIS-TN-IDE/2020;;, Master thesis, 2020-07-15)
      Space-crafts and their instruments tend to collect way more data on their missions than what can be transmitted back to earth in a timely manner. This leads to the need to prioritize what data is to be downloaded and what ...

    • Analysis of Residential Household Energy Consumption Using Smart Meter Data 

      Nwemambu, Chibuzor Valentina (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06-15)
      The need to change the source of electricity generation is apparent in the effect of climate change on the environment. Asides from the source change to renewable energy, the necessity for residents to understand their ...

    • Automated Diagnosis of Prostate Cancer Using mpMRI Images: A Deep Learning Approach for Clinical Decision Support 

      Gavade, Anil B.; Nerli, Rajendra; Kanwal, Neel; Gavade, Priyanka A.; Pol, Shridhar Sunilkumar; Rizvi, Syed Tahir Hussain (Peer reviewed; Journal article, 2023)
      Prostate cancer (PCa) is a significant health concern for men worldwide, where early detection and effective diagnosis can be crucial for successful treatment. Multiparametric magnetic resonance imaging (mpMRI) has evolved ...

    • Automated Well Monitoring: Machine Learning and Web Application 

      Zhurda, Anisa (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-06-15)
      The challenge within the oil and gas industry is that of complexity and therefore cost, specifically due to the tough working environments and delays/downtime . Therefore, digitization is proposed as a cost saving opportunity ...

    • Decreasing Manual Workload by Automating SAP Travel Expense Workflows 

      Husebø, Ivan-Louis Miranda; Kvist, Andreas (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 ...

    • Deep Neural Attention for Misinformation and Deception Detection 

      Mishra, Rahul (PhD thesis UiS;, Doctoral thesis, 2021-06)
      At present the influence of social media on society is so much that without it life seems to have no meaning for many. This kind of over-reliance on social media gives an opportunity to the anarchic elements to take undue ...

    • Deployment and Implementation Aspects of Radio Frequency Fingerprinting in Cybersecurity of Smart Grids 

      Awan, Maaz Ali; Dalveren, Yaser; Catak, Ferhat Özgur; Kara, Ali (Peer reviewed; Journal article, 2023)
      Smart grids incorporate diverse power equipment used for energy optimization in intelligent cities. This equipment may use Internet of Things (IoT) devices and services in the future. To ensure stable operation of smart ...

    • Fake News Detection A Deep Neural Network 

      Chennam Lakhsmikumar, Priyanka (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06-15)
      News is an important source of information for people.Identifying the inaccurate news is a difficult problem. Fake news, defined by the New York Times ”as a made-up story with an intention to deceive”, often for a secondary ...

    • Household Power Demand Prediction Using Evolutionary Ensemble Neural Network Pool with Multiple Network Structures 

      Ai, Songpu; Chakravorty, Antorweep; Chunming, Rong (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 ...

    • Improved Machine Learning-Based Predictive Models for Breast Cancer Diagnosis 

      Rasool, Abdur; Bunterngchit, Chayut; Tiejian, Luo; Islam, Md Ruhul; Qu, Qiang; Jiang, Qingshan (Peer reviewed; Journal article, 2022-03)
      Breast cancer death rates are higher than any other cancer in American women. Machine learning-based predictive models promise earlier detection techniques for breast cancer diagnosis. However, making an evaluation for ...

    • Intelligent supply and demand for marine protein factory (based on MindSphere platform) 

      Heidari, Paria (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06-23)
      The purpose of this project is to collect Internet Of Things data from available sources in the value chain. Our viewpoint to observe IoT data streams from all different processes in the factory as well as get an ...

    • Kvalifisering av smartklokke til bruk i HLR 

      Hove, Andreas (Masteroppgave/UIS-TN-IDE/2017;, Master thesis, 2017-06-15)
      I denne oppgaven ble en smartklokke benyttet til å analysere brystkompresjoner ved hjerte-lunge-redning (HLR). Det ble utviklet to metoder for å måle dybde og rate i brystkompresjoner. Metodene ble verifisert i to eksperiment; ...

    • Optimalisering av gangmønster for firebeint robot med en genetisk algoritme 

      Line, Hartvik (Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-07-15)
      Virveldyr har igjennom evolusjon utviklet kompliserte sentrale mønstergeneratorer (CPG) i sentralnervesystemet for lokomosjon for å avlaste hjernen med sykliske arbeidsoppgaver. Innen robotikk er det interessant å etterligne ...

    • Predicting popularity of Reddit posts using machine learning 

      Wigsnes, Fredrik (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06)
      Using data from the social network Reddit, we see if there are ways to predict if a submission will gain popularity, going into detail in components of a Reddit post, and try to determine if it will be successful. Analyzing ...

    • Sannsynlighetsmodell for monitorering av kvalitet av hjertekompresjoner basert på sammenheng mellom kvalitetsparametre for hjertelungeredning og fysiologisk respons 

      Stokka, Svein Erik (Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-06-15)
      Bakgrunn: Plutselig hjertestans utenfor sykehus er en alvorlig medisinsk tilstand, hvor det i Norge er rundt 3200 tilfeller hvert år. For å overleve hjertestans er det viktig med tidlig og god hjertelungeredning(HLR). Ved ...

    • Secure and Privacy Driven Energy Data Analytics 

      Jose, Dhanya Therese (PhD thesis UiS;, Doctoral thesis, 2022-11)
      Renewable resources are the main energy sources in a smart grid project. In order to ensure the smooth functioning of the smart grid, Information and Communication Technologies (ICT) need to be utilised efficiently. The ...

    • Segmentation of infarcted regions in Perfusion CT images by 3D deep learning 

      Tomasetti, Luca (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06)
      This thesis explores different Convolutional Neural Network (CNN) approaches to classify and segment infarcted regions from images taken through a Computed Tomography Perfusion (CTP) from patients of the Stavanger’s hospital ...

    • Short-Term Load Forecasting Using Smart Meter Data: A Generalization Analysis 

      Mehdipourpirbazari, Aida; Farmanbar, Mina; Chakravorty, Antorweep; Chunming, Rong (Peer reviewed; Journal article, 2020-04)
      Short-term load forecasting ensures the efficient operation of power systems besides affording continuous power supply for energy consumers. Smart meters that are capable of providing detailed information on buildings ...

    • Smart Meter Based Load Forecasting for Residential Customers Using Machine Learning Algorithms 

      Resulaj, Redjol (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 ...