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We construct a hybrid quantum-classical approach for the $K$-Nearest Neighbour algorithm, where the information is embedded in a phase-distributed multimode coherent state with the assistance of a single photon. The task of finding the…

Quantum Physics · Physics 2024-04-19 Vivek Mehta , Francesco Petruccione , Utpal Roy

We present an end-to-end trainable approach for Optical Character Recognition (OCR) on printed documents. Specifically, we propose a model that predicts a) a two-dimensional character grid (\emph{chargrid}) representation of a document…

Computer Vision and Pattern Recognition · Computer Science 2020-02-28 Christian Reisswig , Anoop R Katti , Marco Spinaci , Johannes Höhne

Enormous activity in the Quantum Computing area has resulted in considering them to solve different difficult problems, including those of applied nature, together with classical computers. An attempt is made in this work to nail down a…

We introduce an algorithm for combinatorial search on quantum computers that is capable of significantly concentrating amplitude into solutions for some NP search problems, on average. This is done by exploiting the same aspects of problem…

Quantum Physics · Physics 2007-05-23 Tad Hogg

We introduce an algorithm for combinatorial search on quantum computers that is capable of significantly concentrating amplitude into solutions for some NP search problems, on average. This is done by exploiting the same aspects of problem…

Artificial Intelligence · Computer Science 2009-09-25 T. Hogg

We demonstrated the detailed construction of the hybrid quantum-classical computer. Based on this architecture, the useful concept of amplitude interception is illustrated. It is then embedded into a combination of Depth-First Search and…

Quantum Physics · Physics 2022-10-13 Haoxiang Guo

Medical images are characterized by intricate and complex features, requiring interpretation by physicians with medical knowledge and experience. Classical neural networks can reduce the workload of physicians, but can only handle these…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Yangyang Li , Zhengya Qia , Yuelin Lia , Haorui Yanga , Ronghua Shanga , Licheng Jiaoa

The classical image segmentation algorithm based on grayscale morphology can effectively segment images with uneven illumination, but with the increase of the image data, the real-time problem will emerge. In order to solve this problem, a…

Quantum Physics · Physics 2024-05-14 Wenjie Liu , Lu Wang , Mengmeng Cui

In this paper, we consider a quantum algorithm for solving the following problem: ``Suppose $f$ is a function given as a black box (that is also called an oracle) and $f$ is invariant under some AND-mask. Examine a property of $f$ by…

Quantum Physics · Physics 2007-05-23 Hiroo Azuma

The problem of optical character recognition, OCR, has been widely discussed in the literature. Having a hand-written text, the program aims at recognizing the text. Even though there are several approaches to this issue, it is still an…

Computer Vision and Pattern Recognition · Computer Science 2014-11-07 Wei Wang

An efficient decoding algorithm named `divided decoder' is proposed in this paper. Divided decoding can be combined with any decoder using QR-decomposition and offers different pairs of performance and complexity. Divided decoding provides…

Information Theory · Computer Science 2009-01-23 In Sook Park

Image processing is a fascinating field for exploring quantum algorithms. However, achieving quantum speedups turns out to be a significant challenge. In this work, we focus on image filtering to identify a class of images that can achieve…

Quantum Physics · Physics 2023-08-01 Zidong Cui , Shan Jin , Akira Sone , Xiaoting Wang

A quantum algorithm is a set of instructions for a quantum computer, however, unlike algorithms in classical computer science their results cannot be guaranteed. A quantum system can undergo two types of operation, measurement and quantum…

Data Structures and Algorithms · Computer Science 2007-05-30 Eva Borbely

Hybrid quantum-classical machine learning offers a promising direction for advancing automated quality control in industrial settings. In this study, we investigate two hybrid quantum-classical approaches for classifying defects in…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Akshaya Srinivasan , Xiaoyin Cheng , Jianming Yi , Alexander Geng , Desislava Ivanova , Andreas Weinmann , Ali Moghiseh

Machines are possible to have some artificial intelligence like human beings owing to particular algorithms or software. Such machines could learn knowledge from what people taught them and do works according to the knowledge. In practical…

Quantum Physics · Physics 2015-04-16 Li Zhaokai , Liu Xiaomei , Xu Nanyang , Du jiangfeng

Given two sets A and B and two oracles O(A) and O(B) that can identify the elements of these sets respectively, the goal is to find an element common to both sets using minimum number of oracle queries. Each application of either O(A) or…

Quantum Physics · Physics 2012-10-18 Avatar Tulsi

Quantum machine learning has established as an interdisciplinary field to overcome limitations of classical machine learning and neural networks. This is a field of research which can prove that quantum computers are able to solve problems…

Quantum Physics · Physics 2023-03-13 Meghashrita Das , Tirupati Bolisetti

We introduce a hybrid machine-learning algorithm for designing quantum optics experiments that produce specific quantum states. Our algorithm successfully found experimental schemes to produce all 5 states we asked it to, including…

Quantum Physics · Physics 2019-03-01 L. O'Driscoll , R. Nichols , P. A. Knott

Optical Character Recognition software (OCR) are important tools for obtaining accessible texts. We propose the use of artificial neural networks (ANN) in order to develop pattern recognition algorithms capable of recognizing both normal…

Neural and Evolutionary Computing · Computer Science 2016-07-08 Giuseppe Airò Farulla , Tiziana Armano , Anna Capietto , Nadir Murru , Rosaria Rossini

Fitting geometric models onto outlier contaminated data is provably intractable. Many computer vision systems rely on random sampling heuristics to solve robust fitting, which do not provide optimality guarantees and error bounds. It is…

Computer Vision and Pattern Recognition · Computer Science 2022-06-28 Anh-Dzung Doan , Michele Sasdelli , David Suter , Tat-Jun Chin