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Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration, Goh


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Цена: 7685.00р.
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При оформлении заказа до: 2025-09-29
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Автор: Goh
Название:  Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration
ISBN: 9789819980871
Издательство: Springer
Классификация:




ISBN-10: 9819980879
Обложка/Формат: Soft cover
Страницы: 271
Вес: 0.00 кг.
Дата издания: 14.12.2023
Серия: Lecture notes in computer science
Язык: English
Издание: 1st ed. 2023
Иллюстрации: 41 illustrations, color; 18 illustrations, black and white; xvii, 271 p. 59 illus., 41 illus. in color.
Размер: 235 x 155
Основная тема: Computer Science
Подзаголовок: 25th international conference on asia-pacific digital libraries, icadl 2023, taipei, taiwan, december 4вђ“7, 2023, proceedings, part ii
Ссылка на Издательство: Link
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Поставляется из: Германии


Generative Adversarial Networks and Deep Learning Theory and Applications

Автор: Edited By Roshani Raut, Pranav D Pathak, Sachin R
Название: Generative Adversarial Networks and Deep Learning Theory and Applications
ISBN: 1032068108 ISBN-13(EAN): 9781032068107
Издательство: Taylor&Francis
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Цена: 22968.00 р.
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Описание: This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks, which includes creating new tools and methods for processing text, images, and audio. A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications.

Generative Adversarial Networks(GANs) have the feasibility to build improved models, as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology, including computer vision, security, multimedia and advertisements, image generation, image translation,text-to-images synthesis, video synthesis, generating high-resolution images, drug discovery, etc. Features:Presents a comprehensive guide on how to use GAN for images and videos.

Includes case studies of Underwater Image Enhancement Using Generative Adversarial Network, Intrusion detection using GANHighlights the inclusion of gaming effects using deep learning methodsExamines the significant technological advancements in GAN and its real-world application. Discusses as GAN challenges and optimal solutionsThe book addresses scientific aspects for a wider audience such as junior and senior engineering, undergraduate and postgraduate students, researchers, and anyone interested in the trends development and opportunities in GAN and Deep Learning. The material in the book can serve as a reference in libraries, accreditation agencies, government agencies, and especially the academic institution of higher education intending to launch or reform their engineering curriculum

Generative Artificial Intelligence

Автор: Jerry Kaplan
Название: Generative Artificial Intelligence
ISBN: 0197773540 ISBN-13(EAN): 9780197773543
Издательство: Oxford Academ
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Цена: 2058.00 р.
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Machine Learning

Автор: Tony Jebara
Название: Machine Learning
ISBN: 1461347564 ISBN-13(EAN): 9781461347569
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Machine Learning: Discriminative and Generative covers the main contemporary themes and tools in machine learning ranging from Bayesian probabilistic models to discriminative support-vector machines.

Hands-On Generative Adversarial Networks with PyTorch 1.x

Автор: Hany John, Walters Greg
Название: Hands-On Generative Adversarial Networks with PyTorch 1.x
ISBN: 1789530512 ISBN-13(EAN): 9781789530513
Издательство: Неизвестно
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Цена: 8091.00 р.
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Описание: This book will help you understand how GANs architecture works using PyTorch. You will get familiar with the most flexible deep learning toolkit and use it to transform ideas into actual working codes. You will apply GAN models to areas like computer vision, multimedia and natural language processing using a sample-generation perspective.

Generative AI

Автор: Taulli
Название: Generative AI
ISBN: 148429369X ISBN-13(EAN): 9781484293690
Издательство: Springer
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Цена: 7685.00 р.
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Описание: This book will show how generative technology works and the drivers. It will also look at the applications – showing what various startups and large companies are doing in the space. There will also be a look at the challenges and risk factors. During the past decade, companies have spent billions on AI. But the focus has been on applying the technology to predictions – which is known as analytical AI. It can mean that you receive TikTok videos that you cannot resist. Or analytical AI can fend against spam or fraud or forecast when a package will be delivered. While such things are beneficial, there is much more to AI. The next megatrend will be leveraging the technology to be creative. For example, you could take a book and an AI model will turn it into a movie – at very little cost. This is all part of generative AI. It’s still in the nascent stages but it is progressing quickly. Generative AI can already create engaging blog posts, social media messages, beautiful artwork and compelling videos. The potential for this technology is enormous. It will be useful for many categories like sales, marketing, legal, product design, code generation, and even pharmaceutical creation. What You Will Learn The importance of understanding generative AI The fundamentals of the technology, like the foundation and diffusion models How generative AI apps work How generative AI will impact various categories like the law, marketing/sales, gaming, product development, and code generation. The risks, downsides and challenges. Who This Book is For Professionals that do not have a technical background. Rather, the audience will be mostly those in Corporate America (such as managers) as well as people in tech startups, who will need an understanding of generative AI to evaluate the solutions.

Generative Adversarial Networks Cookbook

Автор: Kalin Josh
Название: Generative Adversarial Networks Cookbook
ISBN: 1789139902 ISBN-13(EAN): 9781789139907
Издательство: Неизвестно
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Цена: 9010.00 р.
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Описание: Generative Adversarial Networks have opened up many new possibilities in the machine learning domain. This book is all you need to implement different types of GANs using TensorFlow and Keras, in order to provide optimized and efficient deep learning solutions.

Deep Generative Models, and Data Augmentation, Labelling, and Imperfections: First Workshop, DGM4MICCAI 2021, and First Workshop, DALI 2021, Held in C

Автор: Engelhardt Sandy, Oksuz Ilkay, Zhu Dajiang
Название: Deep Generative Models, and Data Augmentation, Labelling, and Imperfections: First Workshop, DGM4MICCAI 2021, and First Workshop, DALI 2021, Held in C
ISBN: 3030882098 ISBN-13(EAN): 9783030882099
Издательство: Springer
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Цена: 9083.00 р.
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Описание: This book constitutes the refereed proceedings of the First MICCAI Workshop on Deep Generative Models, DG4MICCAI 2021, and the First MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2021, held in conjunction with MICCAI 2021, in October 2021.

Creative Prototyping with Generative AI

Автор: Parra Pennefather
Название: Creative Prototyping with Generative AI
ISBN: 1484295781 ISBN-13(EAN): 9781484295786
Издательство: Springer
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Цена: 6986.00 р.
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Описание: Reimagine different generative AI as useful creative prototyping tools that can be used to augment your own creative process and projects. Gain a deeper understanding of how generative AI can elevate your creative future. You will acquire a comprehensive understanding of how AI works, uncover tools that can enhance your AI interactions, learn how to extract maximum potential from AI-produced content, and experiment with methods for assessing, refining, and boosting the content to transform your creative projects. You'll also explore how creative professionals from varied disciplines are employing generative AI in their workflows to produce distinctive contributions to the world. Each chapter provides examples of how designers and other creative individuals can utilize these technological wonders, adopting various prototyping techniques to fast-track and optimize design processes and workflows. Creators from all disciplines can tap into the vast capabilities and benefits of generative AI, enabling them to rapidly experiment and prototype their ideas. You Will Learn: * Understand how generative AI can support your own creative process * Learn tools to get the most out of text-text, text-image, and text-video generative AI * Augment your design practices using generative AI * Draw inspiration from AI generated content to create unique creative work * Improve and streamline creatives processes and workflows Who This Book Is For * Digital media professionals who want to access off-the shelf creative tools to improve and accelerate their creativity and workflow. * Designers and engineers who are looking at novel ways to improve their prototyping and testing processes. * Students who want to use AI to rapidly generate ideas to support them in prototyping assignments. * Instructors interested in pointing their students to a variety of accessible AI resources to manage their own creativity.

Interfaceless

Автор: Olynick
Название: Interfaceless
ISBN: ISBN-13(EAN): 9798868800825
Издательство: Springer
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Цена: 6986.00 р.
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Deep Generative Modeling

Автор: Tomczak
Название: Deep Generative Modeling
ISBN: 3030931609 ISBN-13(EAN): 9783030931605
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This textbook tackles the problem of formulating AI systems by combining probabilistic modeling and deep learning. Moreover, it goes beyond typical predictive modeling and brings together supervised learning and unsupervised learning. The resulting paradigm, called deep generative modeling, utilizes the generative perspective on perceiving the surrounding world. It assumes that each phenomenon is driven by an underlying generative process that defines a joint distribution over random variables and their stochastic interactions, i.e., how events occur and in what order. The adjective "deep" comes from the fact that the distribution is parameterized using deep neural networks. There are two distinct traits of deep generative modeling. First, the application of deep neural networks allows rich and flexible parameterization of distributions. Second, the principled manner of modeling stochastic dependencies using probability theory ensures rigorous formulation and prevents potential flaws in reasoning. Moreover, probability theory provides a unified framework where the likelihood function plays a crucial role in quantifying uncertainty and defining objective functions. Deep Generative Modeling is designed to appeal to curious students, engineers, and researchers with a modest mathematical background in undergraduate calculus, linear algebra, probability theory, and the basics in machine learning, deep learning, and programming in Python and PyTorch (or other deep learning libraries). It will appeal to students and researchers from a variety of backgrounds, including computer science, engineering, data science, physics, and bioinformatics, who wish to become familiar with deep generative modeling. To engage the reader, the book introduces fundamental concepts with specific examples and code snippets. The full code accompanying the book is available on github. The ultimate aim of the book is to outline the most important techniques in deep generative modeling and, eventually, enable readers to formulate new models and implement them.

Generative ai: the insights you need from harvard business review

Автор: Harvard Business Review Mollick, Ethan Cremer, David De Neeley, Tsedal Sinha, Prabhakant
Название: Generative ai: the insights you need from harvard business review
ISBN: 164782639X ISBN-13(EAN): 9781647826390
Издательство: INGRAM PUBLISHER SERVICES UK
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Цена: 3166.00 р.
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Generative Methods for Social Media Analysis

Автор: Matwin
Название: Generative Methods for Social Media Analysis
ISBN: 303133616X ISBN-13(EAN): 9783031336164
Издательство: Springer
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Цена: 6288.00 р.
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Описание: This book provides a broad overview of the state of the art of the research in generative methods for the analysis of social media data. It especially includes two important aspects that currently gain importance in mining and modelling social media: dynamics and networks. The book is divided into five chapters and provides an extensive bibliography consisting of more than 250 papers. After a quick introduction and survey of the book in the first chapter, chapter 2 is devoted to the discussion of data models and ontologies for social network analysis. Next, chapter 3 deals with text generation and generative text models and the dangers they pose to social media and society at large. Chapter 4 then focuses on topic modelling and sentiment analysis in the context of social networks. Finally, Chapter 5 presents graph theory tools and approaches to mine and model social networks. Throughout the book, open problems, highlighting potential future directions, are clearly identified. The book aims at researchers and graduate students in social media analysis, information retrieval, and machine learning applications.


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