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QoE-Aware Resource Allocation For Crowdsourced Live Streaming: A Machine Learning Approach
(Computing, 2019 , Master Thesis)
In the last decade, empowered by the technological advancements of mobile devices
and the revolution of wireless mobile network access, the world has witnessed an
explosion in crowdsourced live streaming. Ensuring a ...
Automated Segmentation of Cerebral Aneurysm Using a Novel Statistical Multiresolution Approach
(Computing, 2018 , Master Thesis)
Cerebral Aneurysm (CA) is a vascular disease that threatens the lives of
many adults. It a ects almost 1:5 - 5% of the general population. Sub-
Arachnoid Hemorrhage (SAH), resulted by a ruptured CA, has high rates ...
Latent Semantic Indexing (LSI) Based Distributed System and Search On Encrypted Data
(Computing, 2018 , Master Thesis)
Latent semantic indexing (LSI) was initially introduced to overcome the issues of synonymy and polysemy of the traditional vector space model (VSM). LSI, however, has challenges of its own, mainly scalability. Despite being ...
ON RELEVANCE FILTERING FOR REAL-TIME TWEET SUMMARIZATION
(Computer Science, 2018 , Master Thesis)
Real-time tweet summarization systems (RTS) require mechanisms for capturing relevant tweets, identifying novel tweets, and capturing timely tweets. In this thesis, we tackle the RTS problem with a main focus on the relevance ...
A Deep Learning Based Approach To Detect Covert Channels Attacks and Anomaly In New Generation Internet Protocol IPv6
(Computing, 2020 , Master Thesis)
The increased dependence of internet-based technologies in all facets of life
challenges the government and policymakers with the need for effective shield mechanism
against passive and active violations. Following up ...
Image Steganography Using Deep Learning Methods to Detect Covert Communication in Untrusted Channels
(Computing, 2021 , Master Thesis)
Media has become a primary medium of communication with the help of the constantly evolving technology. Social media like Facebook, YouTube, Twitter, WhatsApp, and other sites have become a platform for exchanging audio, ...
DDI: Drones Detection and Identification using Deep Learning Techniques
(Computing, 2021 , Master Thesis)
Drones are becoming increasingly popular not only for recreational purposes but in day-to-day applications in engineering, medicine, logistics, security and others. Besides their useful applications, an alarming concern ...
Generative Adversarial Networks Based Reconstruction and Restoration of Cultural Heritage
(Computing, 2019 , Master Thesis)
Cultural heritage takes an important part in defining the identity and the
history of a civilization or a nation. Valuing and preserving this heritage is thus a top
priority for governments and heritage institutions. ...
SparkIR: a Scalable Distributed Information Retrieval Engine over Spark
(Computing, 2020 , Master Thesis)
Search engines have to deal with a huge amount of data (e.g., billions of
documents in the case of the Web) and find scalable and efficient ways to produce
effective search results. In this thesis, we propose to use ...
Staticand Dynamic Facial Emotion Recognition Using Neural Network Models
(Computing, 2020 , Master Thesis)
Emotion recognition is the process of identifying human emotions. It is made
possible by processing various modalities including facial expressions, speech signals,
biometricsignals,etc. Withtheadvancementsincomputingt ...