论文标题
一种有效的量子古典杂种算法，用于扭曲的字母数字识别
An efficient quantum-classical hybrid algorithm for distorted alphanumeric character identification
论文作者
论文摘要
提出了用于图像处理的算法。所提出的算法可以看作是量子古典杂种算法，可以将字符的低分辨率Bitonal图像从字母数字字符集（A-Z，0-9）转换为高分辨率图像。所提出算法的量子部分有效地利用了Grover的搜索算法的变体，即固定点搜索算法。此外，使用CQASM模拟该算法的量子部分，并通过复杂性分析确定算法的优势。其他分析还表明，与现有的经典，量子和混合算法相比，该方案的光学特征识别方案（OCR）通常以更有效的方式起作用，并且通常以更有效的方式起作用。
An algorithm for image processing is proposed. The proposed algorithm, which can be viewed as a quantum-classical hybrid algorithm, can transform a low-resolution bitonal image of a character from the set of alphanumeric characters (A-Z, 0-9) into a high-resolution image. The quantum part of the proposed algorithm fruitfully utilizes a variant of Grover's search algorithm, known as the fixed point search algorithm. Further, the quantum part of the algorithm is simulated using CQASM and the advantage of the algorithm is established through the complexity analysis. Additional analysis has also revealed that this scheme for optical character recognition (OCR) leads to high confidence value and generally works in a more efficient manner compared to the existing classical, quantum, and hybrid algorithms for a similar task.
