Quantum computation for large-scale image classification |
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Authors: | Yue Ruan Hanwu Chen Jianing Tan Xi Li |
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Affiliation: | 1.School of Computer Science and Engineering,Southeast University,Nanjing,China;2.School of Computer Science and Technology,Anhui University of Technology,Maanshan,China;3.Key Laboratory of Computer Network and Information Integration,Southeast University, Ministry of Education,Nanjing,China |
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Abstract: | Due to the lack of an effective quantum feature extraction method, there is currently no effective way to perform quantum image classification or recognition. In this paper, for the first time, a global quantum feature extraction method based on Schmidt decomposition is proposed. A revised quantum learning algorithm is also proposed that will classify images by computing the Hamming distance of these features. From the experimental results derived from the benchmark database Caltech 101, and an analysis of the algorithm, an effective approach to large-scale image classification is derived and proposed against the background of big data. |
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