Conference poster
Quantum Artificial Intelligence Predictions Enhancement by Improving Signal Processing
Quantum Australia Conference, 2022 (Sydney, Australia, 23-Feb-2022–25-Feb-2022)
2022
Abstract
Quantum computers have a great potential to change the future of Artificial Intelligence (AI). Although classical supercomputers have powerful processing systems and are efficient for AI applications, the processing speed limit in existing computer systems is still a challenge. Quantum computers (QC) are inspired from nature, that exhibits quantum phenomena of the Superposition and Entanglement. Algorithms designed for QC like Shor’s and Groover have achieved polynomial speed over classical computers. This has attracted many researchers worldwide to investigate the problem and to design more robust algorithms for QC, that are challenge for classical computer. Intelligent Transportation System (ITS) has recently attracted many researchers, to develop fast smart vehicles and smart traffic systems. Reliable, accurate and timely prediction is a major goal of any AI application like traffic flow prediction and delay in predictions can cause unfavourable results. QCs have potential to process huge amount of data for timely prediction. AI deep learning algorithms e.g., Neural Networks (NN), can deal with the processing of complex image data and time series signals.
Details
- Title
- Quantum Artificial Intelligence Predictions Enhancement by Improving Signal Processing
- Authors
- Farina Riaz (Author) - University of Southern QueenslandShahab Abdulla (Author) - University of Southern QueenslandWei Ni (Author) - Commonwealth Scientific and Industrial Research OrganisationRadfar Mohsen (Author) - La Trobe UniversityRavinesh C Deo (Author) - University of Southern QueenslandSusan Hopkins - University of Southern Queensland
- Conference details
- Quantum Australia Conference, 2022 (Sydney, Australia, 23-Feb-2022–25-Feb-2022)
- Date published
- 2022
- Organisation Unit
- School of Education and Tertiary Access
- Language
- English
- Record Identifier
- 991144439702621
- Output Type
- Conference poster
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