Improving information fusion in deep learning
Madduma Kankanamalage Don, Darshana Priyasad (2023) Improving information fusion in deep learning. PhD by Publication, Queensland University of Technology.
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Darshana Priyasad Madduma Kankanamalage Don Thesis. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. |
Description
As humans, we effortlessly use information obtained from multiple sensory perceptions when making decisions or responding. However, even with the explosive growth in the area of deep machine learning, Artificial Intelligence systems struggle to effectively fuse multisensory and multi-modal information to improve the overall performance of intelligent systems. This research has contributed to the creation of new knowledge with respect to information fusion by demonstrating the applicability of the novel fusion techniques that we developed to a wide range of tasks in the fields of human-computer interaction and automated diagnosis of diseases.
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| ID Code: | 241291 |
|---|---|
| Item Type: | QUT Thesis (PhD by Publication) |
| Supervisor: | Sridharan, Sridha, Fookes, Clinton, Denman, Simon, & Warnakulasuriya, Tharindu |
| Keywords: | Multi-modal Information Fusion, Emotion Recognition, Bio-signal Processing, Explicit Memory Networks, Graph-based Fusion |
| DOI: | 10.5204/thesis.eprints.241291 |
| Pure ID: | 139189006 |
| Divisions: | Current > QUT Faculties and Divisions > Faculty of Engineering Current > Schools > School of Electrical Engineering & Robotics |
| Institution: | Queensland University of Technology |
| Deposited On: | 10 Jul 2023 17:19 |
| Last Modified: | 18 Jan 2025 00:48 |
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