Department of Electrical and Computer Engineering (TN-IDE): Nye registreringer

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    • Vision transformers for small histological datasets learned through knowledge distillation 

      Kanwal, Neel; Eftestøl, Trygve Christian; Khoraminia, Farbod; Zuiverloon, Tahlita C M; Engan, Kjersti (Chapter, 2023)
      Computational Pathology (CPATH) systems have the potential to automate diagnostic tasks. However, the artifacts on the digitized histological glass slides, known as Whole Slide Images (WSIs), may hamper the overall performance ...

    • Availability model of a 5G-MEC system 

      Pathirana, Thilina Dhanushka Kalahe; Nencioni, Gianfranco (Chapter, 2023)
      Multi-access Edge Computing (MEC) is one of the enabling technologies of the fifth generation (5G) of mobile networks. MEC enables services with strict latency requirements by bringing computing capabilities close to the ...

    • Analysis of Machine Learning Based Imputation of Missing Data 

      Rizvi, Syed Tahir Hussain; Latif, Muhammad Yasir; Amin, Muhammad Saad; Telmoudi, Achraf Jabeur; Shah, Nasir Ali (Peer reviewed; Journal article, 2023)
      Data analysis and classification can be affected by the availability of missing data in datasets. To deal with missing data, either deletion- or imputation-based methods are used that result in the reduction of data records ...

    • MigraMEC: Hybrid Testbed for MEC App Migration 

      Wadatkar, Prachi Vinod; Garroppo, Rosario G.; Nencioni, Gianfranco (Chapter, 2023)
      Multi-access Edge Computing (MEC) enhances the capabilities of 5G by enabling the computation closer to the end-user for real-time and context-aware services. One of the main challenges of MEC is the migration of the MEC ...

    • NLP-Based Dementia Detection 

      Taleb Zadeh, Abolfazl (Master thesis, 2023)
      This thesis addresses a critical component of Alzheimer's disease (AD) diagnosis by utilizing transcripts of condensed speech data from Dementia Bank. The work uses pre-trained big language models and creates efficient ...

    • Joint multi-objective MEH selection and traffic path computation in 5G-MEC systems 

      Wadatkar, Prachi Vinod; Garroppo, Rosario G.; Nencioni, Gianfranco; Volpi, Marco (Peer reviewed; Journal article, 2024)
      Multi-access Edge Computing (MEC) is an emerging technology that allows to reduce the service latency and traffic congestion and to enable cloud offloading and context awareness. MEC consists in deploying computing devices, ...

    • Evaluation Study of Inertial Positioning in Road Tunnels for Cooperative ITS Applications 

      Martin Rodriguez, Aitor; Khademi, Naeem (Peer reviewed; Journal article, 2023)
      Global Navigation Satellite Systems (GNSS) are unreliable positioning sources in road tunnels, as the satellite signals are unable to reach deep inside the tunnels. As innovative technologies emerge within the transportation ...

    • Revenue-Model Learning for a Slice Broker in the Presence of Adversaries 

      Khan, Md Muhidul Islam; Nencioni, Gianfranco (Chapter, 2023)
      Multi-Access Edge Computing (MEC) and network slicing two of the key enabling technologies of the Fifth Generation (5G) of cellular network. MEC helps to reduce latency, offload the cloud, and allow context-awareness. ...

    • Revenue Maximization of a Slice Broker in the Presence of Byzantine Faults 

      Khan, Md Muhidul Islam; Nencioni, Gianfranco (Chapter, 2023)
      Multi-Access Edge Computing (MEC) and network slicing are vital for advancing the Fifth Generation (5G) of cellular systems. MEC provides context awareness and reduces the latency for communication. Network slicing allows ...

    • Thesis title: Automated Computerized 2D and 3D Characterization of Tumors in Prostate Cancer 

      Alzurkani Rihab (Master thesis, 2023)
      The diagnostic pathway of Prostate cancer (PC) has been changed recently, and medical imaging has gained a significant role. Especially, Magnetic Resonance Imaging (MRI) has emerged as a pivotal tool in advancing cancer ...

    • CT Perfusion is All We Need: 4D CNN Segmentation of Penumbra and Core in Patients With Suspected Acute Ischemic Stroke 

      Tomasetti, Luca; Engan, Kjersti; Høllesli, Liv Jorunn; Kurz, Kathinka Dæhli; Khanmohammadi, Mahdieh (Peer reviewed; Journal article, 2023)
      Stroke is the second leading cause of death worldwide, and around 87 % of strokes are ischemic strokes. Accurate and rapid prediction techniques for identifying ischemic regions, including dead tissue (core) and potentially ...

    • Uncertainty quantification in prostate segmentation 

      Nguyen, Kevin Mekhaphan (Master thesis, 2023)
      Prostate cancer, a significant global health challenge, necessitates innovative diagnostic solutions. Despite the invaluable role of Magnetic Resonance Imaging (MRI), challenges persist in analysis due to time-intensive ...

    • Modelling and Design of Pre-Equalizers for a Fully Operational Visible Light Communication System 

      Bostanoglu, Murat; Dalveren, Yaser; Catak, Ferhat Özgur; Kara, Ali (Peer reviewed; Journal article, 2023-06)
      Nowadays, Visible Light Communication (VLC) has gained much attention due to the significant advancements in Light Emitting Diode (LED) technology. However, the bandwidth of LEDs is one of the important concerns that limits ...

    • Quantification of perineural satellitosis in pretreatment glioblastoma with structural MRI and a diffusion tensor imaging template 

      van den Elshout, Rik; Ariëns, Benthe; Blaauboer, Joost; Meijer, Frederick J A; van der Kolk, Anja G; Esmaeili, Morteza; Scheenen, Tom W J; Henssen, Dylan J H A (Peer reviewed; Journal article, 2023)
      Background Survival outcomes for glioblastoma (GBM) patients remain unfavorable, and tumor recurrence is often observed. Understanding the radiological growth patterns of GBM could aid in improving outcomes. This study ...

    • Resource allocation for cost minimization of a slice broker in a 5G-MEC scenario 

      Sarah, Annisa; Nencioni, Gianfranco (Peer reviewed; Journal article, 2023-11)
      The fifth generation (5G) of mobile networks may offer a custom logical and virtualized network called network slicing. This virtualization opens a new opportunity to share infrastructure resources and encourage cooperation ...

    • 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 ...

    • MRI data-driven clustering reveals different subtypes of Dementia with Lewy bodies 

      Inguanzo, Anna; Poulakis, Konstantinos; Mohanty, Rosaleena; Schwarz, Christopher G.; Przybelski, Scott A.; Diaz-Galvan, Patricia; Lowe, Val J.; Boeve, Bradley F.; Lemstra, Afina W.; van de Beek, Marleen; van der Flier, Wiesje; Barkhof, Frederik; Blanc, Frederic; Loureiro de Sousa, Paulo; Philippi, Nathalie; Cretin, Benjamin; Demuynck, Catherine; Nedelska, Zuzana; Hort, Jakub; Segura, Barbara; Junque, Carme; Oppedal, Ketil; Aarsland, Dag; Westman, Eric; Kantarci, Kejal; Ferreira, Daniel (Peer reviewed; Journal article, 2023)
      Dementia with Lewy bodies (DLB) is a neurodegenerative disorder with a wide heterogeneity of symptoms, which suggests the existence of different subtypes. We used data-driven analysis of magnetic resonance imaging (MRI) ...

    • Kernel recursive least squares dictionary learning algorithm 

      Alipoor, Ghasem; Skretting, Karl (Peer reviewed; Journal article, 2023)
      An online dictionary learning algorithm for kernel sparse representation is developed in the current paper. In this framework, the input signal nonlinearly mapped into the feature space is sparsely represented based on a ...

    • Recurrent Neural Networks for Artifact Correction in HRV Data During Physical Exercise 

      Svane, Jakob; Wiktorski, Tomasz; Ørn, Stein; Eftestøl, Trygve Christian (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 ...

    • Automatic AI-Driven segmentation of Acute Ischemic Stroke Regions with CT Perfusion Images 

      Tomasetti, Luca (PhD thesis UiS;, Doctoral thesis, 2023)
      This thesis investigates artificial intelligence (AI) methodologies to automatically delineate ischemic areas of brain Computed Tomography Perfusion (CTP) scans acquired at hospital admission in patients suspected of acute ...