Browsing by Supervisor
Now showing items 1-20 of 20
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Applying Deep learning techniques - masked facial recognition in smartphone security systems using transfer learning
(Dublin Business School, 2021)Face recognition is the most reliable security measure in smartphones. Face masks make face detection more challenging. In most countries the wearing of facial masks is mandatory on public transport and in public areas to ... -
Artificial narrow intelligence adaptive audio processing
(Dublin Business School, 2019)The age of AI is engulfing us with experts attempting to envision a future driven by the rise of this far-reaching technology. Significant progress has been made during 2018-2019 for AI and deep learning in particular. ... -
Classification of retinal pathology from OCT images using a parametric tuned CNN
(Dublin Business School, 2020)Optometrists nowadays use optical biopsy to get cross sectional images of the retina infected by pathologies. This is also known as Optical Coherence Tomography (OCT). It is important to identify the retinal diseases at ... -
Comparative analysis of deep and transfer learning techniques for two and multi-class weather image classification
(Dublin Business School, 2021)Information about the weather plays a very vital role in day-to-day life of humans, including various sectors like agriculture, business, traffic etc., knowing the weather beforehand helps to resolve several weather-related ... -
Comparative study of Latent Dirichlet allocation and Louvain modularity on topic extraction from Pharma News
(Dublin Business School, 2020)This research compares the efficacy of topic extraction on news content using Latent Dirichlet Allocation (LDA), a traditional method of topic extraction based on Bayesian statistics versus Louvain modularity, a graph-based ... -
Comparative study of traditional and deep learning algorithms on social media using sentiment analysis
(Dublin Business School, 2022)In recent years, there has been a significant increase in social media content. This study focuses on sentiment analysis of Twitter data. This research has been done to improve the accuracy of the sentiment analysis varying ... -
Comparison of machine learning V/S deep learning model to predict ICD9 code using text mining techniques
(Dublin Business School, 2021)Healthcare information is usually collected and stored in form of numbers, texts or images. This data consists of important details such as their visits, symptoms, prescriptions, notes or vital statistics of the patients. ... -
Contact Tracing using Graph Algorithms and exploring graph analytics in a Graph Database (Neo4j)
(Dublin Business School, 2022)The SARS-COVID-19 epidemic is still spreading rapidly globally. Contact Tracing has played an important role during this emergency in identifying the people most likely to be high spreaders of the virus. Graph Data Science ... -
A context-aware personalized recommender system for automation in IoT based smart home environment
(Dublin Business School, 2020)An IoT enabled smart-home fulfils many needs of the inhabitants such as providing conveniences through personalised home automation, saving energy through optimizations, etc., based mostly on the user’s behaviour and ... -
Exploring the space of topic modelling and topic coherence on short and long text corpora
(Dublin Business School, 2020)Topic Modelling, a discipline of Natural Language Processing, is widely prevalent and its application on social network communications has become essential in identifying key themes impacting society. In this dissertation ... -
Implementation of clustering algorithm using graph embeddings and graph data science on Yelp restaurant dataset
(Dublin Business School, 2020)This research uses the leading property graph DBMS, Neo4j to implement a Restaurant Knowledge Graph of the Yelp Dataset (Challenge 2020 – business; users; category; reviews). The application of CYPHER queries; graph ... -
Improvement of recall measure by deriving graph features for link prediction on machine learning algorithms
(Dublin Business School, 2019)In recent years the volume of data has increased significantly creating new challenges and opportunities in dealing with the interconnected data. Although new technologies enable the processing of high volumes of ... -
Performance evaluation of ensemble based recommendation system using biased matrix factorization and content based filtering
(Dublin Business School, 2020)Boosting product sales is the primary objective of any Recommender System and it is achieved by providing users a personalized recommendation from the world of information density and product overload. The suggestions ... -
Prediction of patient's health risk in critical care using a deep neural network
(Dublin Business School, 2020)The Intensive care units (ICU’s) of a hospital comprise a large share of the health care budget as today’s lifestyle habits and environmental conditions contribute to the onset of chronic diseases. High risk patients in ... -
Real time fraud detection using streaming batches & implementation of a real time data warehouse subtitle: a combined approach to machine learning & data storage
(Dublin Business School, 2020)Anomaly detection is becoming increasingly more important in sectors like banking, medicine, computer networks and many more. The volume of online transactions is increasing exponentially, and credit card online transactions ... -
Real-time face detection using histogram of oriented gradients, convolutional neural networks and feature extraction to enhance the online shopping experience
(Dublin Business School, 2019)Recent trends in technology shows that computer vision has become an integral part of all artificial intelligence projects. Ranging from a normal barcode scanner to real-time CCTV surveillance and to self-driving cars, the ... -
Stock price prediction using time series models
(Dublin Business School, 2019)This Thesis titled- “Stock price forecasting using time series models” focused on the comparison of the performance of time series models to predict the stock price for 5 banks. Forecasting and stock price analysis is ... -
A study of ensemble machine learning to improve telecommunication customer churn prediction
(Dublin Business School, 2020)The telecom industry has an ever-increasing number of service providers. With the competition between service providers to attract more customers by making attractive offers, there is an incentive for customers to keep ... -
Topic modelling and theme discovery on Aylien News articles during COVID-19
(Dublin Business School, 2020)Topic modelling is increasingly important for the analysis of large volumes of unlabelled data necessitating scanning a collection of documents and identifying keywords and language usage patterns. It is a technique of ... -
Yelp rating classification using connected graph feature extraction and feature importance in machine learning workflow
(Dublin Business School, 2019)This thesis titled- “Yelp Rating Classification Using Connected Graph Feature Extraction and Feature Importance In Machine Learning Workflow” focused on Yelp’s Challenge Dataset Round 13, we analyze data about restaurants ...