Search results for "IKT591"
showing 7 items of 7 documents
3D Convolution Neural Networks for Medical Imaging; Classification and Segmentation : A Doctor’s Third Eye
2020
Master's thesis in Information- and communication technology (IKT591) In this thesis, we studied and developed 3D classification and segmentation models for medical imaging. The classification is done for Alzheimer’s Disease and segmentation is for brain tumor sub-regions. For the medical imaging classification task we worked towards developing a novel deep architecture which can accomplish the complex task of classifying Alzheimer’s Disease volumetrically from the MRI scans without the need of any transfer learning. The experiments were performed for both binary classification of Alzheimer’s Disease (AD) from Normal Cognitive (NC), as well as multi class classification between the three st…
Ultra Reliable Communication in 5G Networks: A Dependability-based Availability Analysis in the Space Domain
2017
Master's thesis Information- and communication technology IKT591 - University of Agder 2017 As our daily life is becoming more dependent on wireless and mobile services, seamless network connectivity is of utmost importance. Wireless networks are expected to handle the growing demand for applications which require higher capacity, without failure. Therein, wireless connectivity is regarded as an essential requirement for a wide range of applications in order to support exible and cost-e ective services. As part of the fth generation (5G) communication paradigm, ultra reliable communication (URC) is envisaged as an important technology pillar for providing anywhere and anytime services to en…
MAC Protocols for WuR Enabled WSNs : Design and Performance Evaluation
2017
Master's thesis Information- and communication technology IKT591 - University of Agder 2017 Increasing energy efficiency is a challenging task for protocol design in wireless sensor networks (WSNs) as well as in Internet of things (IoT). Traditionally, duty-cycled (DC) protocols have been widely adopted for data transmissions in WSNs for energy conservation by reducing idle listening and overhearing. Recently, wake-up radio (WuR) has merged as a promising technique to replace DC protocols thanks to its superior performance in both network lifetime and transmission latency. This thesis work focuses on the design and performance evaluation of WuR-enabled MAC protocols considering various traf…
Design and implementation of wake-up radios for long-range wireless IoT devices
2019
Master's thesis Information- and communication technology IKT591 - University of Agder 2019 As the development within Internet of things IoT increases rapidly andthe market starts to utilize its potential, an enormous effort is being madein both academia and industry to optimize solutions according to the mar-ket demands. The demands vary from case to case. Some applicationsmight require relatively high data rate, long battery lifetime, low latencyand long range/area coverage. The numerous use cases and demands for IoTresulted in various IoT technologies. In many IoT applications, especiallyWireless IoT applications, energy-efficiency and battery lifetime are some ofthe most important perfo…
Learning Automata-Based Object Partitioning with Pre-Specified Cardinalities
2020
Master's thesis in Information- and communication technology (IKT591) The Object Migrating Automata (OMA) has been used as a powerful AI-based tool to resolve real-life partitioning problems. Apart from its original version, variants and enhancements that invoke the pursuit concept of Learning Automata, and the phenomena of transitivity, have more recently been used to improve its power. The single major handicap that it possesses is the fact that the number of the objects in each partition must be equal. This thesis deals with the task of relaxing this constraint. Thus, in this thesis, we will consider the problem of designing OMA-based schemes when the number of the objects can be unequal…
A Scalable Architecture for Parallel Execution of the Tsetlin Machine
2019
Master's thesis Information- and communication technology IKT591 - University of Agder 2019 With the Tsetlin Machine recently released, much research has been done on itscapabilities, with great success. However, the lack of tools available, and generalknowledge of the Tsetlin Machine prevents it from being adopted by the indus-try. As a result, it is today mostly used in academic environments. To increasethe general availability of the algorithm, this thesis introduces an introductorydescription to the algorithm and proposes an architecture that allows the use ofmultiple CPU threads and multiple GPUs to execute the algorithm in parallel. Inaddition, this thesis investigates several key asp…
Classification of Diabetes and Cardiac Arrhythmia using Deep Learning
2018
Master's thesis Information- and communication technology IKT591 - University of Agder 2018 Deep Learning (DL) is a research area that has ourished signi cantly in the recent years and has shown remarkable potential for arti cial intelligence in the eld of medical applications. The reasons for success are the ability of DL algorithms to model high-level abstractions in the data by using automatic feature extraction property as well as signi cant amount of medical data that is available for training these algorithms. DL algorithms can learn features from a large volume of healthcare data, and then use the procured insights to assist clinical practice. We have implement DL algorithm for the c…