Now showing items 281-300 of 823

    • Evaluating Computer Vision Methods for Detection and Pose Estimation of Textureless Objects 

      Skutvik, Harald Thirud (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06)
      Robotics, AI and automation; search for these words and two things become apparent. An era of automation is upon us, but even so there are still some simple tasks that grinds it to a halt, e.g. picking and placing objects. ...
    • Evaluating Fairness in Information Retrieval Systems: A Study on the Performance of the FAIR Metric 

      Eriksen, Maria (Master thesis, 2023)
      In the digital era, the use of information retrieval (IR) technologies has surged, enabling users to access vast amounts of data quickly. However, concerns have arisen regarding bias and unfairness in these systems, leading ...
    • Evaluation of low-cost software-defined LTE/5G frameworks: cloudification 

      Håland, Mari (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06)
      There has been a tremendous rise in mobile communication units over the past decade. Where cellphones once dominated the user market for fast wireless communication solutions, we now see an abundance of devices and appliances ...
    • Event-triggered and self-triggered control of a 3 DOF hover system 

      Normann, Vetle (Master thesis, 2023)
      Many modern control systems are implemented on devices that are resource constrained in the form of computational power, energy consumption or bandwidth. Control systems are conventionally implemented through periodic ...
    • Evolving Deep Neural Networks for Continuous Learning: Addressing Challenges and Adapting to Changing Data Conditions without Catastrophic Forgetting 

      Atamanczuk, Bruna; Karadas, Kurt Arve Skipenes (Master thesis, 2023)
      Continuous learning plays a crucial role in advancing the field of machine learning by addressing the challenges posed by evolving data and complex learning tasks. This thesis presents a novel approach to address the ...
    • Exploring Generative Adversarial Networks to Improve Prostate Segmentation on MRI 

      Larsen, Steinar Valle (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-06-28)
      Prostate cancer is the second most occurring cancer and the sixth leading cause of cancer death among men worldwide. The number of cases is expected to increase dramatically due to population growth and increased expected ...
    • Exploring the Potential use of Convolutional Neural Networks for Clinically Significant Prostate Cancer Detection through the lens of age 

      Eidissen, Kristoffer; Cardenas, Juan Sebastian (Bachelor thesis, 2023)
      Prostate Cancer (PCa) represents a significant public health challenge in developed nations, with over 5,000 men being diagnosed with the disease annually in Norway alone, rendering it the most frequently occurring cancer ...
    • Extending enterprise architecture models for cloud computing 

      Pantiuchovas, Dmitrijus (Masteroppgave/UIS-TN-IDE/2012;, Master thesis, 2012)
      The new wave of technology changes has introduced cloud computing. For an enterprise this innovation can bring great cost savings as well as risks. Therefore a special analysis process shall be done before the decision is ...
    • Extending the Snarl File Repair Component for Distributed Storage Systems 

      Stavnes, Eivind; Urdal, Daniel (Master thesis, 2021)
      This thesis extends the Snarl file repair component for distributed storage systems, and evaluates extensions. Snarl is an application using alpha entanglement codes to improve recovery rates of content stored in distributed ...
    • Extending the Snarl File Repair Component for Distributed Storage Systems 

      Stavnes, Eivind; Urdal, Daniel (Master thesis, 2021)
      This thesis extends the Snarl file repair component for distributed storage systems, and evaluates extensions. Snarl is an application using alpha entanglement codes to improve recovery rates of content stored in distributed ...
    • Extracting coronary arteries in angiographic images 

      Moene, Alexander Kvale (Masteroppgave/UIS-TN-IDE/2017;, Master thesis, 2017-07-15)
      This master thesis has as propose to extract coronary arteries form angiographic video. With several stability issues with the easy to implement established functions in the time domain and other methods that is far too ...
    • Fact Checking using Knowledge Bases 

      Khurshid Adil; Ramesh Apoorva (Master thesis, 2022)
      In today’s society, the spread of incorrect information is becoming an increasingly serious issue. Verifying information using unstructured data, such as a text corpus, can be difficult for all claims since they lack ...
    • Fact-Checking using Knowledge bases 

      Ramesh, Apoorva; Khurshid, Adil (Master thesis, 2022)
      In today's society, the spread of incorrect information is becoming an increasingly serious issue. Verifying information using unstructured data, such as a text corpus, can be difficult for all claims since they lack ...
    • Fairness and Ethics in AI 

      Chakravorty Antorweep (Bachelor thesis, 2021)
      As the complexity and capabilities of AI technologies continue to increase, they will continue to pose a risk for their users. In this thesis, different techniques have been reviewed to see how the current research proposes ...
    • Fairness and Interpretability in Machine Learning Models 

      Weinbach, Bjørn Christian (Master thesis, 2022)
      Machine Learning has become more and more prominent in our daily lives as the Information Age and Fourth industrial revolution progresses. Many of these machine learning systems are evaluated in terms of how accurately ...
    • Fake News Data Generation and Augmentation 

      Botnevik, Bjarte (Master thesis, 2021)
      Fake news is becoming an increasingly more significant problem in today's society, especially on social media. The fact-checking field in Data Science is becoming more and more popular as people want to solve this. However, ...
    • 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 ...
    • Fast and Reliable Byzantine Fault Tolerance 

      Freeman, Eric (Masteroppgave/UIS-TN-IDE/2016;, Master thesis, 2016-06)
      Byzantine faults, or arbitrary faults, are difficult to handle due to their unknown nature. They include software errors, hardware errors, and malicious behavior. There are several algorithms which handle Byzantine faults ...
    • Feature extraction for exploring infarcted regions in perfusion CT images of the brain 

      Hovland, Eivind (Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-06-15)
      In Norway, over 15 000 people suffer from acute cerebral stroke annually, it is the leading cause of adult long-term severe disability and a significant reason for admission to nursing homes. In Norway it is a prominent ...
    • Federated Learning for Dementia Classification in a European Multicentre Dementia Study 

      Hesseberg, Ruben; Minne, Petter (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-07-15)
      Every year around 10 million people are diagnosed with dementia worldwide. Higher life expectancy and population growth could inflate this number even further in the near future. Currently the diagnostic process of dementia ...