Quantum Convolutional Neural Network for Medical Image Classification: A Hybrid Model
- Title
- Quantum Convolutional Neural Network for Medical Image Classification: A Hybrid Model
- Creator
- Khatoniar R.; Vyas V.; Acharya V.; Saxena A.; Saxena A.; Neiwal R.; Korgaonkar K.
- Description
- This study explores the application of Quantum Convolutional Neural Networks (QCNNs) in the realm of image classification, particularly focusing on datasets with a highly reduced number of features. We investigate the potential quantum computing holds in processing and classifying image data efficiently, even with limited feature availability. This research investigates QCNNs' application within a highly constrained feature environment, using chest X-ray images to distinguish between normal and pneumonia cases. Our findings demonstrate QCNNs' utility in classifying images from the dataset with drastically reduced feature dimensions, highlighting QCNNs' robustness and their promising future in machine learning and computer vision. Additionally, this study sheds light on the scalability of QCNNs and their adaptability across various training-test splits, emphasizing their potential to enhance computational efficiency in machine learning tasks. This suggests a possibility of paradigm shift in how we approach data-intensive challenges in the era of quantum computing. We are looking into quantum paradigms like Quantum Support Vector Machine (QSVM) going forward so that we can explore trade offs effectiveness of different classical and quantum computing techniques. 2024 IEEE.
- Source
- TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024
- Date
- 2024-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- quantum computer architecture; Quantum computing; quantum machine learning; quantum neural networks
- Coverage
- Khatoniar R., Bits Pilani, Csis Department, K K Birla Goa Campus Goa, India; Vyas V., C-DAC Pune, Pune, India; Acharya V., Bits Pilani, Csis Department, K K Birla Goa Campus Goa, India; Saxena A., Christ University, Bengaluru, India; Saxena A., C-DAC Pune, Pune, India; Neiwal R., MeitY (Delhi), Delhi, India; Korgaonkar K., Bits Pilani, Csis Department, K K Birla Goa Campus Goa, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835038427-7
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Khatoniar R.; Vyas V.; Acharya V.; Saxena A.; Saxena A.; Neiwal R.; Korgaonkar K., “Quantum Convolutional Neural Network for Medical Image Classification: A Hybrid Model,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/19180.