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Hybrid deep learning with stacked dilated causal convolutions for health forecasting using multivariate time-series data
(2022)
Health forecasting using time-series data facilitates preventive medicine and healthcare interventions by predicting future health events. This thesis introduces a novel
hybrid deep-learning architecture for health ...
3D GPU-based image reconstruction algorithm for the application in a clinical organ-targeted PET camera
(2022)
Functional medical imaging is unique in its ability to visualize molecular interactions and
pathways in the body. Organ-targeted Positron Emission Tomography (PET) is a
functional imaging technique that has emerged to ...
Multi-timeframe algorithmic trading bots using thick data heuristics with deep reinforcement learning
(2022)
This thesis presents an augmented Artificial Intelligence (AI) algorithmic trading
approach that combines Thick Data Heuristics (TDH), with Deep Reinforcement Learning
(DRL), to successfully learn trading execution timing ...
Quantifying the impact of Twitter activity in political battlegrounds
(2022)
It may be challenging to determine the reach of the information, how well it corresponds with
the domain design, and how to utilize it as a communication medium when utilizing social
media platforms, notably Twitter, to ...
Boosting feature extraction performance on the aspect of representation learning efficiency
(2022)
Machine learning is famous for its automatic data handling. While there is a
slow growth in the performance of the state-of-the-art models in the most recent
well-known learning frameworks, the number of parameters and ...
Enhancing machine vision using human cognition from EEG analysis
(2022)
Visual classification is the perceptible/computational effort of arranging objects and visual
contexts into distinct labels. Humans and machines have mastered this advanced problem in
their own varied contexts. However, ...