[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118430-en":3,"doc-seo-118430-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},118430,687197207057,"Sage","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","piQture - A Quantum Machine Learning Library for Image Processing - Master Thesis","Quantum Machine Learning (QML) studies how quantum information and machine learning can combine quantum properties to improve computation. As QML tools move toward real-world deployments, integrating QML models into a complete machine-learning workflow for tasks like image processing becomes essential. This thesis surveys QML models, evaluates their practical utility for image-related problems, and uses the results to build a robust library. The work develops piQture, an open-source Python and Qiskit-based framework for streamlining design, training, evaluation, and reproducible software engineering, including automated build, test, and packaging pipelines, plus strategies for model management and storage.","piQture: A Quantum Machine Learning Library for Image Processing  \nby  \nSaasha Joshi  \nB.E., University Institute of Engineering and Technology Panjab University, 2021  \nA Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of  \nMaster of Science  \nin the Department of Computer Science  \n© Saasha Joshi, 2024 University of Victoria  \nAll rights reserved. This thesis may not be reproduced in whole or in part, by photocopying or other means, without the permission of the author.  \nii  \npiQture: A Quantum Machine Learning Library for Image Processing  \nby  \nSaasha Joshi  \nB.E., University Institute of Engineering and Technology Panjab University, 2021  \nSupervisory Committee  \nDr. Hausi A. M¨uller, Co-Supervisor (Department of Computer Science)  \nDr. Ulrike Stege, Co-Supervisor (Department of Computer Science)  \niii  \nSupervisory Committee  \nDr. Hausi A. M¨uller, Co-Supervisor (Department of Computer Science)  \nDr. Ulrike Stege, Co-Supervisor (Department of Computer Science)  \nABSTRACT  \nQuantum Machine Learning (QML) is a discipline of research at the intersection of quantum information and machine learning that leverages quantum mechanical properties to enhance computational capabilities. With its emergence, there is a need to integrate QML models into machine learning pipelines for real-life applications such as image processing. While standalone programs exist to demonstrate the performance of QML models, a well-defined model workflow is noticeably absent. This thesis thoroughly explores various existing QML models and their practical utility in image processing tasks, with the aim of constructing a robust QML library.  \nThroughout this thesis, we develop piQture, an open-source Python and Qiskitbased library that streamlines the development, training, and evaluation of QML models. Its design and structure prioritize usability among users familiar with classical machine learning without prior QML experience. Further, piQture is augmented with automated building, testing, and packaging workflows that enhance software reliability and reproducibility. Finally, we provide strategies to facilitate model management and storage within piQture for practical adoption and future analysis of pre-trained QML models.  \niv  \nTable of Contents  \nSupervisory Committee ii  \nAbstract iii  \nTable of Contents iv  \nList of Tables vii  \nList of Figures viii  \nGlossary xiii  \nAcknowledgements xv  \n1 Introduction 1  \n1.1 Motivation ................................. 2  \n1.2 Problem Definition and Research Questions .............. 2  \n1.3 Contributions ............................... 3  \n1.4 Our Approach ............................... 3  \n1.5 Outline ................................... 4  \n2 Background and Related Work 5  \n2.1 Data Embedding ............................. 5  \n2.1.1 Quantum Image Representations ................ 6  \n2.2 QML Algorithms for Image Classification ................ 13  \n2.2.1 Quantum Support Vector Machines ............... 13  \n2.2.2 Kernel Methods .......................... 14  \n2.2.3 Variational Quantum Algorithms ................ 14  \n2.2.4 Quantum Tensor Networks .................... 15  \n2.2.5 Quantum Neural Networks .................... 20  \nv  \n2.3 QML Workflows .............................. 24  \n3 Quantum Image Representation 27  \n3.1 Overview .................................. 27  \n3.2 QIR Methods ............................... 29  \n4 Quantum Machine Learning 38  \n4.1 Quantum Feature Maps and Kernels .................. 38  \n4.1.1 Example: Pauli Feature Map .................. 39  \n4.2 Kernel Methods .............................. 41  \n4.2.1 Support Vector Machines ..................... 41  \n4.2.2 Example: Quantum Kernel Estimator .............. 45  \n4.3 Variational Quantum Algorithms .................... 46  \n4.3.1 Example: Variational Quantum Classifier ............ 47  \n4.4 Quantum Tensor Networks ........................ 49  \n4.4.1 Example: Hierarchical Quantum Classifier ........... 50  \n4","cbCaicsuFUsQex7r","https://ap.wps.com/l/cbCaicsuFUsQex7r","pdf",10654819,1,138,"English","en",105,"# Supervisory Committee\n# Abstract\n# Table of Contents\n# List of Tables\n# List of Figures\n# Glossary\n# Acknowledgements\n# Introduction\n## Motivation\n## Problem Definition and Research Questions\n## Contributions\n## Our Approach\n## Outline\n# Background and Related Work\n## Data Embedding\n### Quantum Image Representations\n## QML Algorithms for Image Classification\n### Quantum Support Vector Machines\n### Kernel Methods\n### Variational Quantum Algorithms\n### Quantum Tensor Networks\n### Quantum Neural Networks\n## QML Workflows\n# Quantum Image Representation\n## Overview\n## QIR Methods\n# Quantum Machine Learning\n## Quantum Feature Maps and Kernels\n### Example: Pauli Feature Map\n## Kernel Methods\n### Support Vector Machines\n### Example: Quantum Kernel Estimator\n## Variational Quantum Algorithms\n### Example: Variational Quantum Classifier\n## Quantum Tensor Networks\n### Example: Hierarchical Quantum Classifier\n## Quantum Neural Networks\n### Example: Quantum Convolutional Neural Network\n# Introducing piQture\n## Overview\n## Pipeline Design\n### Workflow Description\n## Pipeline Structure\n### Data Preprocessing\n### Quantum Circuit Preparation Stage\n### Quantum Circuit Processing Stage\n### Measurement\n# Advancing piQture: Strategies for CI/CD\n## Overview\n## Building, Testing, and Packaging piQture\n### Setting Up the GitHub Repository\n### Building\n### Testing\n### Packaging\n## piQture in Production\n### Model Management\n### Prediction Service\n# Quick Start Guide: How to use piQture?\n## Getting Started\n### Setup\n### Installation\n### Installation from Source\n## Tutorials\n### Tutorial 1: Building an INEQR encoding\n### Tutorial 2: Building a TTN tensor network\n### Tutorial 3: Training a QCNN model\n# Conclusion and Future Work\n## Contributions\n## Future Work\n### Optimizing piQture Design and Structure\n### Workflow Management and Monitoring\n### Model Evaluation Techniques","[{\"question\":\"What problem does the thesis address regarding QML and image processing?\",\"answer\":\"It addresses the lack of a well-defined model workflow for integrating QML models into machine-learning pipelines for practical image-processing applications.\"},{\"question\":\"What is piQture and what does it streamline?\",\"answer\":\"piQture is an open-source Python and Qiskit-based library that streamlines the development, training, and evaluation of QML models, with a design focused on usability for users familiar with classical ML.\"},{\"question\":\"How does the thesis improve software reliability and reproducibility for piQture?\",\"answer\":\"It adds automated building, testing, and packaging workflows (CI/CD) and provides strategies for managing and storing models to support practical adoption and future analysis.\"}]","piQture - A Quantum Machine Learning Library for Image Processing - Master Thesis | PDF",1785683575,348,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"piqture-a-quantum-machine-learning-library-for-image-processing-master-thesis","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/piqture-a-quantum-machine-learning-library-for-image-processing-master-thesis/118430/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05","2026-08-02",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What problem does the thesis address regarding QML and image processing?","Question",{"text":76,"@type":77},"It addresses the lack of a well-defined model workflow for integrating QML models into machine-learning pipelines for practical image-processing applications.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What is piQture and what does it streamline?",{"text":81,"@type":77},"piQture is an open-source Python and Qiskit-based library that streamlines the development, training, and evaluation of QML models, with a design focused on usability for users familiar with classical ML.",{"name":83,"@type":74,"acceptedAnswer":84},"How does the thesis improve software reliability and reproducibility for piQture?",{"text":85,"@type":77},"It adds automated building, testing, and packaging workflows (CI/CD) and provides strategies for managing and storing models to support practical adoption and future analysis.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":46,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":46,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]