Meta Learning Frameworks For Imaging Applications
DOWNLOAD eBooks
Download Meta Learning Frameworks For Imaging Applications PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Meta Learning Frameworks For Imaging Applications book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Meta Learning Frameworks For Imaging Applications
DOWNLOAD eBooks
Author : Sharma, Ashok
language : en
Publisher: IGI Global
Release Date : 2023-09-28
Meta Learning Frameworks For Imaging Applications written by Sharma, Ashok and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-28 with Computers categories.
Meta-learning, or learning to learn, has been gaining popularity in recent years to adapt to new tasks systematically and efficiently in machine learning. In the book, Meta-Learning Frameworks for Imaging Applications, experts from the fields of machine learning and imaging come together to explore the current state of meta-learning and its application to medical imaging and health informatics. The book presents an overview of the meta-learning framework, including common versions such as model-agnostic learning, memory augmentation, prototype networks, and learning to optimize. It also discusses how meta-learning can be applied to address fundamental limitations of deep neural networks, such as high data demand, computationally expensive training, and limited ability for task transfer. One critical topic in imaging is image segmentation, and the book explores how a meta-learning-based framework can help identify the best image segmentation algorithm, which would be particularly beneficial in the healthcare domain. This book is relevant to healthcare institutes, e-commerce companies, and educational institutions, as well as professionals and practitioners in the intelligent system, computational data science, network applications, and biomedical applications fields. It is also useful for domain developers and project managers from diagnostic and pharmacy companies involved in the development of medical expert systems. Additionally, graduate and master students in intelligent systems, big data management, computational intelligent approaches, computer vision, and biomedical science can use this book for their final projects and specific courses.
Meta Learning With Medical Imaging And Health Informatics Applications
DOWNLOAD eBooks
Author : Hien Van Nguyen
language : en
Publisher: Academic Press
Release Date : 2022-09-24
Meta Learning With Medical Imaging And Health Informatics Applications written by Hien Van Nguyen and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-24 with Computers categories.
Meta-Learning, or learning to learn, has become increasingly popular in recent years. Instead of building AI systems from scratch for each machine learning task, Meta-Learning constructs computational mechanisms to systematically and efficiently adapt to new tasks. The meta-learning paradigm has great potential to address deep neural networks’ fundamental challenges such as intensive data requirement, computationally expensive training, and limited capacity for transfer among tasks. This book provides a concise summary of Meta-Learning theories and their diverse applications in medical imaging and health informatics. It covers the unifying theory of meta-learning and its popular variants such as model-agnostic learning, memory augmentation, prototypical networks, and learning to optimize. The book brings together thought leaders from both machine learning and health informatics fields to discuss the current state of Meta-Learning, its relevance to medical imaging and health informatics, and future directions. First book on applying Meta Learning to medical imaging Pioneers in the field as contributing authors to explain the theory and its development Has GitHub repository consisting of various code examples and documentation to help the audience to set up Meta-Learning algorithms for their applications quickly
Meta Learning
DOWNLOAD eBooks
Author : Lan Zou
language : en
Publisher: Elsevier
Release Date : 2022-11-05
Meta Learning written by Lan Zou and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-05 with Computers categories.
Deep neural networks (DNNs) with their dense and complex algorithms provide real possibilities for Artificial General Intelligence (AGI). Meta-learning with DNNs brings AGI much closer: artificial agents solving intelligent tasks that human beings can achieve, even transcending what they can achieve. Meta-Learning: Theory, Algorithms and Applications shows how meta-learning in combination with DNNs advances towards AGI. Meta-Learning: Theory, Algorithms and Applications explains the fundamentals of meta-learning by providing answers to these questions: What is meta-learning?; why do we need meta-learning?; how are self-improved meta-learning mechanisms heading for AGI ?; how can we use meta-learning in our approach to specific scenarios? The book presents the background of seven mainstream paradigms: meta-learning, few-shot learning, deep learning, transfer learning, machine learning, probabilistic modeling, and Bayesian inference. It then explains important state-of-the-art mechanisms and their variants for meta-learning, including memory-augmented neural networks, meta-networks, convolutional Siamese neural networks, matching networks, prototypical networks, relation networks, LSTM meta-learning, model-agnostic meta-learning, and the Reptile algorithm. The book takes a deep dive into nearly 200 state-of-the-art meta-learning algorithms from top tier conferences (e.g. NeurIPS, ICML, CVPR, ACL, ICLR, KDD). It systematically investigates 39 categories of tasks from 11 real-world application fields: Computer Vision, Natural Language Processing, Meta-Reinforcement Learning, Healthcare, Finance and Economy, Construction Materials, Graphic Neural Networks, Program Synthesis, Smart City, Recommended Systems, and Climate Science. Each application field concludes by looking at future trends or by giving a summary of available resources. Meta-Learning: Theory, Algorithms and Applications is a great resource to understand the principles of meta-learning and to learn state-of-the-art meta-learning algorithms, giving the student, researcher and industry professional the ability to apply meta-learning for various novel applications. A comprehensive overview of state-of-the-art meta-learning techniques and methods associated with deep neural networks together with a broad range of application areas Coverage of nearly 200 state-of-the-art meta-learning algorithms, which are promoted by premier global AI conferences and journals, and 300 to 450 pieces of key research Systematic and detailed exploration of the most crucial state-of-the-art meta-learning algorithm mechanisms: model-based, metric-based, and optimization-based Provides solutions to the limitations of using deep learning and/or machine learning methods, particularly with small sample sizes and unlabeled data Gives an understanding of how meta-learning acts as a stepping stone to Artificial General Intelligence in 39 categories of tasks from 11 real-world application fields
Automated Machine Learning And Meta Learning For Multimedia
DOWNLOAD eBooks
Author : Wenwu Zhu
language : en
Publisher: Springer Nature
Release Date : 2022-01-01
Automated Machine Learning And Meta Learning For Multimedia written by Wenwu Zhu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-01 with Computers categories.
This book disseminates and promotes the recent research progress and frontier development on AutoML and meta-learning as well as their applications on computer vision, natural language processing, multimedia and data mining related fields. These are exciting and fast-growing research directions in the general field of machine learning. The authors advocate novel, high-quality research findings, and innovative solutions to the challenging problems in AutoML and meta-learning. This topic is at the core of the scope of artificial intelligence, and is attractive to audience from both academia and industry. This book is highly accessible to the whole machine learning community, including: researchers, students and practitioners who are interested in AutoML, meta-learning, and their applications in multimedia, computer vision, natural language processing and data mining related tasks. The book is self-contained and designed for introductory and intermediate audiences. No special prerequisite knowledge is required to read this book.
Learning With Limited Samples
DOWNLOAD eBooks
Author : LISHA CHEN; SHARU THERESA JOSE; IVANA NIKOLOSKA; S.
language : en
Publisher:
Release Date : 2023
Learning With Limited Samples written by LISHA CHEN; SHARU THERESA JOSE; IVANA NIKOLOSKA; S. and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with TECHNOLOGY & ENGINEERING categories.
Deep learning has achieved remarkable success in many machine learning tasks such as image classification, speech recognition, and game playing. However, these breakthroughs are often difficult to translate into real-world engineering systems because deep learning models require a massive number of training samples, which are costly to obtain in practice. To address labeled data scarcity, few-shot meta-learning optimizes learning algorithms that can efficiently adapt to new tasks quickly. While meta-learning is gaining significant interest in the machine learning literature, its working principles and theoretic fundamentals are not as well understood in the engineering community.This review monograph provides an introduction to meta-learning by covering principles, algorithms, theory, and engineering applications. After introducing meta-learning in comparison with conventional and joint learning, the main meta-learning algorithms are described, as well as a general bilevel optimization framework for the definition of meta-learning techniques. Then, known results on the generalization capabilities of meta-learning from a statistical learning viewpoint are summarized. Applications to communication systems, including decoding and power allocation, are discussed next, followed by an introduction to aspects related to the integration of meta-learning with emerging computing technologies, namely neuromorphic and quantum computing. The monograph concludes with an overview of open research challenges.
Artificial Intelligence In The Age Of Nanotechnology
DOWNLOAD eBooks
Author : Jaber, Wassim
language : en
Publisher: IGI Global
Release Date : 2023-12-07
Artificial Intelligence In The Age Of Nanotechnology written by Jaber, Wassim and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-07 with Technology & Engineering categories.
In the world of academia, scholars and researchers are confronted with a rapidly expanding knowledge base in Artificial Intelligence (AI) and nanotechnology. The integration of these two groundbreaking fields presents an intricate web of concepts, innovations, and interdisciplinary applications that can overwhelm even the most astute academic minds. Staying up to date with the latest developments and effectively navigating this complex terrain has become a pressing challenge for those striving to contribute meaningfully to these fields. Artificial Intelligence in the Age of Nanotechnology is a transformative solution meticulously crafted to address the academic community's knowledge gaps and challenges. This comprehensive book serves as the guiding light for scholars, researchers, and students grappling with the dynamic synergy between AI and Nanotechnology. It offers a structured and authoritative exploration of the core principles and transformative applications of these domains across diverse fields. By providing clarity and depth, it empowers academics to stay at the forefront of innovation and make informed contributions.
Handbook Of Research On Ai And Ml For Intelligent Machines And Systems
DOWNLOAD eBooks
Author : Gupta, Brij B.
language : en
Publisher: IGI Global
Release Date : 2023-11-27
Handbook Of Research On Ai And Ml For Intelligent Machines And Systems written by Gupta, Brij B. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-27 with Computers categories.
The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by artificial intelligence (AI) and machine learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths.
Impact Of Ai On Advancing Women S Safety
DOWNLOAD eBooks
Author : Ponnusamy, Sivaram
language : en
Publisher: IGI Global
Release Date : 2024-02-16
Impact Of Ai On Advancing Women S Safety written by Ponnusamy, Sivaram and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-16 with Computers categories.
Women encounter multifaceted threats, ranging from personal safety hazards to discrimination deeply embedded in societal structures. The existing landscape demands innovative strategies to ensure women can participate fully in society without fear or impediment. Traditional systems often fall short, necessitating a paradigm shift in our approach to women's safety. Impact of AI on Advancing Women's Safety emerges as a groundbreaking solution to address the pervasive challenges they face. From the shadows of harassment to systemic biases in justice systems, women navigate a complex landscape. This book delves into the pressing issues, unveiling a visionary approach that leverages artificial intelligence to create tangible, transformative solutions.
Medical Image Computing And Computer Assisted Intervention Miccai 2023
DOWNLOAD eBooks
Author : Hayit Greenspan
language : en
Publisher: Springer Nature
Release Date : 2023-09-30
Medical Image Computing And Computer Assisted Intervention Miccai 2023 written by Hayit Greenspan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-30 with Computers categories.
The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023. The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in the following topical sections: Part I: Machine learning with limited supervision and machine learning – transfer learning; Part II: Machine learning – learning strategies; machine learning – explainability, bias, and uncertainty; Part III: Machine learning – explainability, bias and uncertainty; image segmentation; Part IV: Image segmentation; Part V: Computer-aided diagnosis; Part VI: Computer-aided diagnosis; computational pathology; Part VII: Clinical applications – abdomen; clinical applications – breast; clinical applications – cardiac; clinical applications – dermatology; clinical applications – fetal imaging; clinical applications – lung; clinical applications – musculoskeletal; clinical applications – oncology; clinical applications – ophthalmology; clinical applications – vascular; Part VIII: Clinical applications – neuroimaging; microscopy; Part IX: Image-guided intervention, surgical planning, and data science; Part X: Image reconstruction and image registration.
Advances In Smart Healthcare Paradigms And Applications
DOWNLOAD eBooks
Author : Halina Kwaśnicka
language : en
Publisher: Springer Nature
Release Date : 2023-08-16
Advances In Smart Healthcare Paradigms And Applications written by Halina Kwaśnicka and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-16 with Technology & Engineering categories.
This book is dedicated to showcase research and innovation in smart healthcare systems and technologies led by women scientists, researchers, and practitioners. With the advent of artificial intelligence (AI) and related technologies, the healthcare sector has undergone tremendous changes in practice and management in recent years. On par to men, women have made significant contributions to tackle a variety of healthcare problems, creating smarter paradigms to provide effective and efficient solutions for patients and stakeholders. The book presents a small collection of contributions by outstanding women in STEM (Science, Technology, Engineering and Mathematics) education, focusing on the healthcare domain. The selected articles allow readers to comprehend current advances in AI and other methods for undertaking healthcare challenges. It is envisaged that the inspiring work by prominent women scientists, researchers, and practitioners reported in this book offers a beacon to propel women in pursuing STEM education and advancing the healthcare sector for the benefits of humankind.