MS Theses - DO NOT EDIT: Recent submissions
Now showing items 21-40 of 355
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BLOCKCHAIN: RESOURCE UTILISATION ANALYSIS WITH A GAME THEORY PERSPECTIVE
(2019-05-10)Major blockchain networks are using proof-of-work based consensus protocols to establish trust and decentralize resource management with different incentive mechanisms for the participants or nodes in the network. We ... -
EXPERIMENTAL EVALUATION OF N-MODEL METHODOLOGY
(2019-05-13)Software maintenance is an essential part of the software development life cycle. Usually software engineers use ad hoc approaches to enhance legacy systems in the absence of a systematic methodology. However, there exists ... -
PREDICT BEHAVIOURAL SCORES IN SLEEP APNEA PATIENTS FROM RESTING STATE NEAR-INFRARED SPECTROSCOPY (fNIRS)
(2021-05-07)Sleep disorders are common among adults and children; it has serious consequences on their heath, cognitive development and quality of life. However, some sleep disorders are challenging to diagnose and more challenging ... -
USING SENTIMENT AND EMOTION ANALYSIS OF NEWS ARTICLES TO ANALYZE THE EFFECTS OF LEADER’S STATEMENTS ON COVID-19 SPREAD
(2021-05-09)Leaders generally include government officials, politicians, etc. Their statements can highly affect people’s decisions in many ways. Currently, in the pandemic situation, many statements were being passed every hour and ... -
STRUCTURE AWARE HUMAN POSE ESTIMATION USING ADVERSARIAL LEARNING
(2021-05-10)Pose estimation using Deep Neural Networks (DNNs) has shown outstanding performance in recent years, due to the availability of powerful GPUs and larger training datasets. However, there are still many challenges due to ... -
END-USER FRAMEWORK FOR ROBOT CONTROL
(2021-05-10)This thesis describes in detail a developed end-user framework for a humanrobot collaborative system for common tasks, such as pick and place. The system is designed for semi-automated pick and place tasks as well as manual ... -
LOW-DOSE CT IMAGE DENOISING USING DEEP LEARNING METHODS
(2021-05-07)Low-dose computed tomography (LDCT) has raised highly attention since the counterpart, full-dose computed tomography (FDCT), brings potential ionizing radiation influence to patients. However, LDCT still suffers from several ... -
CONTINUOUS AMERICAN SIGN LANGUAGE TRANSLATION WITH ENGLISH SPEECH SYNTHESIS USING ENCODER-DECODER APPROACH
(2021-05-09)Interaction between human beings brings about improvements in science and technology. However, the interaction is limited for people who are deaf or hard-of-hearing, as they can only communicate with others who also know ... -
LEARNING HIERARCHICAL TRAVERSABILITY REPRESENTATION FOR EFFICIENT MULTI-RESOLUTION PATH PLANNING
(2021-05-13)Path finding on grid-based obstacle maps is an important and much studied problem with applications in robotics and autonomy. Traditionally, in the AI community, heuristic search methods (e.g. based on Dijkstra and A*, or ... -
Towards Location Free Movement Recognition with Channel State Information
(2019-12-03)Channel state information based movement recognition has gathered immense attention over recent years. Different from traditional systems which usually require wearable sensors or surveillance cameras, many existing works ... -
LINK PREDICTION BASED FACE CLUSTERING USING VARIATIONAL ATTENTIONAL GRAPH AUTOENCODER
(2020-12-01)In this work, we address the problem of clustering faces according to their individual identities present inherently in the dataset.The current clustering frameworks are either based on some heuristic method or require ... -
EARLY DETECTION OF GLAUCOMA USING MODIFIED RESIDUAL U-NET CONVOLUTIONAL NEURAL NETWORK
(2020-12-07)Glaucoma is the second leading cause of blindness all over the world, with apparently 75 million cases reported worldwide in 2018. If it’s not diagnosed at an early stage, glaucoma may cause irreversible damage to the optic ... -
INCOMPLETE TIME SERIES FORECASTING USING GENERATIVE NEURAL NETWORKS
(2020-12-07)Dealing with missing data is a long pervading problem and it becomes more challenging when forecasting time series data because of the complex relationships between data and time, which is why incomplete data can lead to ... -
GENERATING ADVERSARIAL EXAMPLES FOR RECRUITMENT RANKING ALGORITHMS
(2020-12-16)There is no doubt that recruitment process plays an important role for both employers and applicants. Based on huge number of job candidates and open vacancies, recruitment process is expensive, time consuming and stressful ... -
SEMI-AUTOMATIC HAND POSE ESTIMATION USING A SINGLE DEPTH CAMERA
(2020-11-30)This paper addresses the problem of 3D hand pose annotations using a single depth camera. Although hand pose estimation methods rely critically on accurate 3D training data, creating such reliable training data is challenging ... -
A Survey on DDoS Attacks in Edge Servers
(2020-12-09)In modern times, the need for latency sensitive applications is growing rapidly. Cloud computing infrastructure is unable to provide support to such delay sensitive applications. Therefore, a new paradigm called edge ... -
ACTIVITY RECOGNITION TO MIMIC HUMAN PERCEPTION
(2020-09-03)The recognition of activities from video is a capability that is important for a wide range of applications, ranging from basic scene understanding to the successful prediction of behavior in autonomous vehicle applications. ... -
In Situ Sensor Calibration Using Noise Consistency
(2020-09-08)Robots rely on sensors to map their surroundings. As a result, the accuracy of the map depends heavily on the sensor noise and in particular on accurate knowledge of it. The common way to ... -
"How Good are They?" - A State of the Effectiveness of Anti-Phishing Tools on Twitter
(2020-07-02)Phishing websites are one of the most pervasive online attack vectors, with nearly 1.5 million such attacks created every month. Social media is the primary ground for phishing attacks, with 86% of these attacks originating ... -
Classification of Factual and Non-Factual Statements Using Adversarially Trained LSTM Networks
(2020-06-08)Being able to determine which statements are factual and therefore likely candidates for further verification is a key value-add in any automated fact-checking system. For this task, it has been shown that LSTMs outperform ...