Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/158142
Title: Quantum machine learning for image classification
Authors: Myat Kaung
Keywords: Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Myat Kaung (2022). Quantum machine learning for image classification. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158142
Project: A2144-211
Abstract: Quantum Machine learning is a promising technology that is related to the study of computing. Due to the property of quantum systems, it has become an area of research that is focused on solving computational problems using quantum parallelism, which can give computational advantages such as faster computational speed, reducing time considerations for classical computing tasks to achieve. By comparison, in classical conventional computation, it can have only two states: if it is ON, it is ‘1’ and if it is OFF, it is ‘0’. Using all the modern computational devices for instance, laptops, computers, and mobile phones use these two simple digits. On the other hand, in quantum computing, there is a special feature called superposition, which allows a quantum bit to be at both ‘0’ and ‘1’ state at the same time. This superposition can be used in parallel processing tasks for example, big data, Machine learning, etc.
URI: https://hdl.handle.net/10356/158142
Schools: School of Electrical and Electronic Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
Myat_Kaung_FYP_Final_Report.pdf
  Restricted Access
Quantum Machine Learning For Image Classification1.76 MBAdobe PDFView/Open

Page view(s)

66
Updated on Dec 4, 2023

Download(s)

11
Updated on Dec 4, 2023

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.