Quantum‐inspired Arecanut X‐ray image classification using transfer learning
Abstract Arecanut X‐ray images accurately represent their internal structure. A comparative analysis of transfer learning‐based classification, employing both a traditional convolutional neural network (CNN) and an advanced quantum convolutional neural network (QCNN) approach is conducted. The inves...
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| Format: | Article |
| Language: | English |
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Wiley
2024-12-01
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| Series: | IET Quantum Communication |
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| Online Access: | https://doi.org/10.1049/qtc2.12099 |
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| author | Praveen M. Naik Bhawana Rudra |
| author_facet | Praveen M. Naik Bhawana Rudra |
| author_sort | Praveen M. Naik |
| collection | DOAJ |
| description | Abstract Arecanut X‐ray images accurately represent their internal structure. A comparative analysis of transfer learning‐based classification, employing both a traditional convolutional neural network (CNN) and an advanced quantum convolutional neural network (QCNN) approach is conducted. The investigation explores various transfer learning models with different sizes to identify the most suitable one for achieving enhanced accuracy. The Shufflenet model with a scale factor of 2.0 attains the highest classification accuracy of 97.72% using the QCNN approach, with a model size of 28.40 MB. Out of the 12 transfer learning models tested, 9 exhibit improved classification accuracy when using QCNN models compared to the traditional CNN‐based transfer learning approach. Consequently, the exploration of CNN and QCNN‐based classification reveals that QCNN outperforms traditional CNN models in accuracy within the transfer learning framework. Further experiments with qubits suggest that utilising 4 qubits is optimal for classification operations in this context. |
| format | Article |
| id | doaj-art-b6f22d81bbc64998aaab965762d7af8a |
| institution | DOAJ |
| issn | 2632-8925 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Quantum Communication |
| spelling | doaj-art-b6f22d81bbc64998aaab965762d7af8a2025-08-20T02:39:38ZengWileyIET Quantum Communication2632-89252024-12-015430330910.1049/qtc2.12099Quantum‐inspired Arecanut X‐ray image classification using transfer learningPraveen M. Naik0Bhawana Rudra1Department of Information Technology National Institute of Technology Karnataka Surathkal, Mangaluru Karnataka IndiaDepartment of Information Technology National Institute of Technology Karnataka Surathkal, Mangaluru Karnataka IndiaAbstract Arecanut X‐ray images accurately represent their internal structure. A comparative analysis of transfer learning‐based classification, employing both a traditional convolutional neural network (CNN) and an advanced quantum convolutional neural network (QCNN) approach is conducted. The investigation explores various transfer learning models with different sizes to identify the most suitable one for achieving enhanced accuracy. The Shufflenet model with a scale factor of 2.0 attains the highest classification accuracy of 97.72% using the QCNN approach, with a model size of 28.40 MB. Out of the 12 transfer learning models tested, 9 exhibit improved classification accuracy when using QCNN models compared to the traditional CNN‐based transfer learning approach. Consequently, the exploration of CNN and QCNN‐based classification reveals that QCNN outperforms traditional CNN models in accuracy within the transfer learning framework. Further experiments with qubits suggest that utilising 4 qubits is optimal for classification operations in this context.https://doi.org/10.1049/qtc2.12099quantum computingquantum information |
| spellingShingle | Praveen M. Naik Bhawana Rudra Quantum‐inspired Arecanut X‐ray image classification using transfer learning IET Quantum Communication quantum computing quantum information |
| title | Quantum‐inspired Arecanut X‐ray image classification using transfer learning |
| title_full | Quantum‐inspired Arecanut X‐ray image classification using transfer learning |
| title_fullStr | Quantum‐inspired Arecanut X‐ray image classification using transfer learning |
| title_full_unstemmed | Quantum‐inspired Arecanut X‐ray image classification using transfer learning |
| title_short | Quantum‐inspired Arecanut X‐ray image classification using transfer learning |
| title_sort | quantum inspired arecanut x ray image classification using transfer learning |
| topic | quantum computing quantum information |
| url | https://doi.org/10.1049/qtc2.12099 |
| work_keys_str_mv | AT praveenmnaik quantuminspiredarecanutxrayimageclassificationusingtransferlearning AT bhawanarudra quantuminspiredarecanutxrayimageclassificationusingtransferlearning |