Synthetic Data For Visual Machine Learning

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Synthetic Data For Visual Machine Learning

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Author : Apostolia Tsirikoglou
language : en
Publisher:
Release Date : 2022

Synthetic Data For Visual Machine Learning written by Apostolia Tsirikoglou and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Electronic books categories.

Synthetic Data For Deep Learning

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Author : Sergey I. Nikolenko
language : en
Publisher: Springer Nature
Release Date : 2021-06-26

Synthetic Data For Deep Learning written by Sergey I. Nikolenko and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-26 with Computers categories.

This is the first book on synthetic data for deep learning, and its breadth of coverage may render this book as the default reference on synthetic data for years to come. The book can also serve as an introduction to several other important subfields of machine learning that are seldom touched upon in other books. Machine learning as a discipline would not be possible without the inner workings of optimization at hand. The book includes the necessary sinews of optimization though the crux of the discussion centers on the increasingly popular tool for training deep learning models, namely synthetic data. It is expected that the field of synthetic data will undergo exponential growth in the near future. This book serves as a comprehensive survey of the field. In the simplest case, synthetic data refers to computer-generated graphics used to train computer vision models. There are many more facets of synthetic data to consider. In the section on basic computer vision, the book discusses fundamental computer vision problems, both low-level (e.g., optical flow estimation) and high-level (e.g., object detection and semantic segmentation), synthetic environments and datasets for outdoor and urban scenes (autonomous driving), indoor scenes (indoor navigation), aerial navigation, and simulation environments for robotics. Additionally, it touches upon applications of synthetic data outside computer vision (in neural programming, bioinformatics, NLP, and more). It also surveys the work on improving synthetic data development and alternative ways to produce it such as GANs. The book introduces and reviews several different approaches to synthetic data in various domains of machine learning, most notably the following fields: domain adaptation for making synthetic data more realistic and/or adapting the models to be trained on synthetic data and differential privacy for generating synthetic data with privacy guarantees. This discussion is accompanied by an introduction into generative adversarial networks (GAN) and an introduction to differential privacy.

Synthetic Data For Deep Learning

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Author : Necmi Gürsakal
language : en
Publisher: Apress
Release Date : 2022-11-16

Synthetic Data For Deep Learning written by Necmi Gürsakal and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-16 with Computers categories.

Data is the indispensable fuel that drives the decision making of everything from governments, to major corporations, to sports teams. Its value is almost beyond measure. But what if that data is either unavailable or problematic to access? That’s where synthetic data comes in. This book will show you how to generate synthetic data and use it to maximum effect. Synthetic Data for Deep Learning begins by tracing the need for and development of synthetic data before delving into the role it plays in machine learning and computer vision. You’ll gain insight into how synthetic data can be used to study the benefits of autonomous driving systems and to make accurate predictions about real-world data. You’ll work through practical examples of synthetic data generation using Python and R, placing its purpose and methods in a real-world context. Generative Adversarial Networks (GANs) are also covered in detail, explaining how they work and their potential applications. After completing this book, you’ll have the knowledge necessary to generate and use synthetic data to enhance your corporate, scientific, or governmental decision making. What You Will Learn Create synthetic tabular data with R and Python Understand how synthetic data is important for artificial neural networks Master the benefits and challenges of synthetic data Understand concepts such as domain randomization and domain adaptation related to synthetic data generation Who This Book Is For Those who want to learn about synthetic data and its applications, especially professionals working in the field of machine learning and computer vision. This book will also be useful for graduate and doctoral students interested in this subject.

Digital Synthetic Data And Outputs

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Author : Hai-Jew, Shalin
language : en
Publisher: IGI Global
Release Date : 2025-11-20

Digital Synthetic Data And Outputs written by Hai-Jew, Shalin and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-20 with Computers categories.

Digital synthetic data and outputs represent an evolving landscape in data science and artificial intelligence (AI), offering alternatives to traditional data collection methods. Synthetic data refers to information that is artificially generated rather than obtained by direct measurement or real-world observation, often using advanced algorithms, simulations, or generative AI models. This approach enables researchers and developers to create datasets free from privacy and ethical concerns tied to real data. As industries rely on AI-driven insights, digital synthetic outputs become essential tools for training, testing, and validating models across sectors like healthcare, finance, and autonomous systems. Digital Synthetic Data and Outputs explores the various applications of digital synthetics, applied across a range of disciplines and fields. It examines how digital synthetic data can enhance automation, communication, and computation. This book covers topics such as big data, game design, and data validation, and is a useful resource for business owners, engineers, academicians, researchers, and computer scientists.

Pattern Recognition And Computer Vision In The New Ai Era

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Author : Chi Hau Chen
language : en
Publisher: World Scientific
Release Date : 2025-07-15

Pattern Recognition And Computer Vision In The New Ai Era written by Chi Hau Chen and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-15 with Computers categories.

While traditional approaches in pattern recognition and computer vision have continued to evolve, along with the advances of artificial intelligence (AI), this unique compendium presents recent research activities in deep learning, graph-based and semantic-based approaches and applications.The book covers the most recent advances as well as traditional topics in pattern recognition and computer vision in this new AI area in the first part. The second part presents emerging applications of deep learning and AI. This useful reference text benefits academics, professionals, researchers and graduate students in pattern recognition, computer vision, image segmentation and artificial intelligence.

Proceedings Of The Canadian Society For Civil Engineering Annual Conference 2023 Volume 4

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Author : Serge Desjardins
language : en
Publisher: Springer Nature
Release Date : 2024-09-17

Proceedings Of The Canadian Society For Civil Engineering Annual Conference 2023 Volume 4 written by Serge Desjardins and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-17 with Technology & Engineering categories.

This book comprises the proceedings of the Annual Conference of the Canadian Society for Civil Engineering 2023. The contents of this volume focus on the specialty track in construction with topics on modular and offsite construction, BIM, construction planning and project management, construction automation, AI and robotics in construction, sustainable construction, asset management, and construction safety, among others. This volume will prove a valuable resource for researchers and professionals.

Synthetic Data For Machine Learning

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Author : Abdulrahman Kerim
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-10-27

Synthetic Data For Machine Learning written by Abdulrahman Kerim and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-27 with Computers categories.

Conquer data hurdles, supercharge your ML journey, and become a leader in your field with synthetic data generation techniques, best practices, and case studies Key Features Avoid common data issues by identifying and solving them using synthetic data-based solutions Master synthetic data generation approaches to prepare for the future of machine learning Enhance performance, reduce budget, and stand out from competitors using synthetic data Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe machine learning (ML) revolution has made our world unimaginable without its products and services. However, training ML models requires vast datasets, which entails a process plagued by high costs, errors, and privacy concerns associated with collecting and annotating real data. Synthetic data emerges as a promising solution to all these challenges. This book is designed to bridge theory and practice of using synthetic data, offering invaluable support for your ML journey. Synthetic Data for Machine Learning empowers you to tackle real data issues, enhance your ML models' performance, and gain a deep understanding of synthetic data generation. You’ll explore the strengths and weaknesses of various approaches, gaining practical knowledge with hands-on examples of modern methods, including Generative Adversarial Networks (GANs) and diffusion models. Additionally, you’ll uncover the secrets and best practices to harness the full potential of synthetic data. By the end of this book, you’ll have mastered synthetic data and positioned yourself as a market leader, ready for more advanced, cost-effective, and higher-quality data sources, setting you ahead of your peers in the next generation of ML.What you will learn Understand real data problems, limitations, drawbacks, and pitfalls Harness the potential of synthetic data for data-hungry ML models Discover state-of-the-art synthetic data generation approaches and solutions Uncover synthetic data potential by working on diverse case studies Understand synthetic data challenges and emerging research topics Apply synthetic data to your ML projects successfully Who this book is forIf you are a machine learning (ML) practitioner or researcher who wants to overcome data problems, this book is for you. Basic knowledge of ML and Python programming is required. The book is one of the pioneer works on the subject, providing leading-edge support for ML engineers, researchers, companies, and decision makers.

Proceedings Of The International Conference On Artificial Intelligence And Computer Vision Aicv2021

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Author : Aboul Ella Hassanien
language : en
Publisher: Springer Nature
Release Date : 2021-05-28

Proceedings Of The International Conference On Artificial Intelligence And Computer Vision Aicv2021 written by Aboul Ella Hassanien and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-28 with Technology & Engineering categories.

This book presents the 2nd International Conference on Artificial Intelligence and Computer Visions (AICV 2021) proceeding, which took place in Settat, Morocco, from June 28- to 30, 2021. AICV 2021 is organized by the Scientific Research Group in Egypt (SRGE) and the Computer, Networks, Mobility and Modeling Laboratory (IR2M), Hassan 1st University, Faculty of Sciences Techniques, Settat, Morocco. This international conference highlighted essential research and developments in the fields of artificial intelligence and computer visions. The book is divided into sections, covering the following topics: Deep Learning and Applications; Smart Grid, Internet of Things, and Mobil Applications; Machine Learning and Metaheuristics Optimization; Business Intelligence and Applications; Machine Vision, Robotics, and Speech Recognition; Advanced Machine Learning Technologies; Big Data, Digital Transformation, AI and Network Analysis; Cybersecurity; Feature Selection, Classification, and Applications.

Computer Vision Eccv 2024 Workshops

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Author : Alessio Del Bue
language : en
Publisher: Springer Nature
Release Date : 2025-05-29

Computer Vision Eccv 2024 Workshops written by Alessio Del Bue and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-29 with Computers categories.

The multi-volume set LNCS 15623 until LNCS 15646 constitutes the proceedings of the workshops that were held in conjunction with the 18th European Conference on Computer Vision, ECCV 2024, which took place in Milan, Italy, during September 29–October 4, 2024. These LNCS volumes contain 574 accepted papers from 53 of the 73 workshops. The list of workshops and distribution of the workshop papers in the LNCS volumes can be found in the preface that is freely accessible online.

Intelligent Vision And Computing

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Author : Apu Kumar Saha
language : en
Publisher: Springer Nature
Release Date : 2026-01-05

Intelligent Vision And Computing written by Apu Kumar Saha and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-05 with Computers categories.

This book includes selected papers presented at 5th International Conference on Intelligent Vision and Computing (ICIVC 2025), held at The ICFAI University, Dehradun, India, during 13–14 June 2025. The conference proceedings is a collection of high-quality research articles in the field of intelligent vision and computing. The topics covered in the book are artificial intelligence, machine learning, deep learning, internet of things, information security, embedded systems, cloud computing, quantum computing, bio-inspired intelligence, cyber-physical systems, hybrid systems, intelligence for security, data mining, evolutionary optimization, swarm intelligence, signal processing, blockchain technology, big data applications, natural language processing, data acquisition, storage and retrieval for big data, data representation, processing, imaging sensors technology, features extraction, image segmentation, deep learning, convolutional neural network, biometrics recognition, biomedical imaging, intelligent transport systems, and human–computer interaction.