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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control)
Prasanalakshmi Balaji
King Khalid University
Computer Science & IT

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Quantum transfer learning for image classification Geetha Subbiah; Shridevi S. Krishnakumar; Nitin Asthana; Prasanalakshmi Balaji; Thavavel Vaiyapuri
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 1: February 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i1.24103

Abstract

Quantum machine learning, an important element of quantum computing, recently has gained research attention around the world. In this paper, we have proposed a quantum machine learning model to classify images using a quantum classifier. We exhibit the results of a comprehensive quantum classifier with transfer learning applied to image datasets in particular. The work uses hybrid transfer learning technique along with the classical pre-trained network and variational quantum circuits as their final layers on a small scale of dataset. The implementation is carried out in a quantum processor of a chosen set of highly informative functions using PennyLane a cross-platform software package for using quantum computers to evaluate the high-resolution image classifier. The performance of the model proved to be more accurate than its counterpart and outperforms all other existing classical models in terms of time and competence.
Co-Authors Geetha Subbiah Nitin Asthana Shridevi S. Krishnakumar Thavavel Vaiyapuri