A quantum-search-based multi-classifier for image recognition  

作　　者：Lu Liu Xingyu Wu Lufan Zhang Chuan Wang 

机构地区：[1]School of Artificial Intelligence,Beijing Normal University,Beijing 100875,China [2]Applied Optics Beijing Area Major Laboratory,Beijing Normal University,Beijing 100875,China

出　　处：《Science China(Physics,Mechanics & Astronomy)》2025年第1期17-27,共11页中国科学:物理学、力学、天文学(英文版)

基　　金：the support from the National Natural Science Foundation of China(Grant Nos.62131002,62305028,and 62071448);the Fundamental Research Funds for the Central Universities(BNU)。

摘　　要：The multi-class classification of images is a pivotal challenge within the realm of image processing.As the volume of visual data continues to expand,there is a burgeoning interest in harnessing the unique capabilities of quantum computation to augment the efficiency of classification tasks.However,many existing methods for training quantum image multi-classifiers parallel classical machine learning techniques,where the requisite circuit measurements increase linearly with the volume of training data.This work introduces a novel approach for training a quantum image multi-classifier based on the quantum search algorithm.We have meticulously conducted rigorous experiments on a handwritten digit dataset,a classic benchmark in the field.The results have been meticulously compared with previous works,and the comparative analysis not only validates the efficiency of our proposed approach,requiring only O(N/b)measurements during training,but also highlights a significant quadratic speedup of the algorithm.

关 键 词：quantum computation image recognition quantum search algorithm 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]