Meta Learning Frameworks For Imaging Applications
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Meta Learning Frameworks For Imaging Applications
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Author : SHARMA
language : en
Publisher:
Release Date : 2023
Meta Learning Frameworks For Imaging Applications written by SHARMA and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Meta Learning Frameworks For Imaging Applications
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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
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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
Exploring Generative Adversarial Networks And Meta Learning Synergies
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Author : Simaiya, Sarita
language : en
Publisher: IGI Global
Release Date : 2025-04-16
Exploring Generative Adversarial Networks And Meta Learning Synergies written by Simaiya, Sarita and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-16 with Computers categories.
Generative Adversarial Networks (GANs) and Meta-Learning synergies can be combined and leveraged to enhance the capabilities of artificial intelligence (AI) systems, particularly in areas such as image generation, style transfer, few-shot learning, and domain adaptation. These techniques can be integrated to develop more robust and efficient AI models. Ultimately, understanding the theoretical foundations, implementation strategies, and practical applications of GANs and Meta-Learning can be used to address complex real-world challenges. Exploring Generative Adversarial Networks and Meta-Learning Synergies explores the intersection and synergy between two cutting-edge AI techniques: GANs and Meta-Learning. It showcases the potential of these synergies in advancing the field of AI and addressing complex real-world challenges. Covering topics such as neuromorphic computing, transfer learning, and visual speech recognition, this book is an excellent resource for computer scientists, entrepreneurs, healthcare professionals, professionals, researchers, scholars, academicians, and more.
Applying Metaverse Technologies To Human Computer Interaction For Healthcare
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Author : B. Sundaravadivazhagan
language : en
Publisher: CRC Press
Release Date : 2025-03-13
Applying Metaverse Technologies To Human Computer Interaction For Healthcare written by B. Sundaravadivazhagan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-13 with Medical categories.
The concept of the metaverse signifies the forthcoming stage of development of the Internet, wherein it will facilitate the creation of virtual worlds that are enduring, decentralized, and capable of providing immersive experiences in real time. The metaverse has vast potential for utilization in the domains of life sciences and healthcare, hence motivating investigations in contemporary trends, early adoption use cases, and the forthcoming opportunities it presents. The metaverse also possesses the capacity to fundamentally transform decentralized clinical trials through the elimination of physical and geographical constraints. This change in thinking entails the relocation of clinical trials from conventional settings to the comfort and convenience of patients’ residences, resulting in improvements in health behavior, medication adherence, remote monitoring, and other associated factors. Applying Metaverse Technologies to Human-Computer Interaction for Healthcare focuses on the current developments in the metaverse, investigates its applications in the life sciences and healthcare industry based on metaverse powered human−computer interactions (HCI), analyzes early adoption use cases that provide measurable commercial benefits, and anticipates prospects in this rapidly evolving domain. The book examines the treatment, management, and prevention of illnesses with the use of immersive therapeutics that use augmented reality (AR), virtual reality (VR), and mixed reality (MR). It examines applications in cognitive therapy, support groups, psychiatric examinations, rehabilitation, and even physical therapy The book covers how healthcare practitioners have the capability to provide such services as diagnosis, treatment, monitoring, and care in remote settings, through the utilization of AR headsets and wearable devices. It concludes by discussing the continuous development of technology to facilitate the growth and maturation of the metaverse, hence enabling substantial business benefits for the life sciences and healthcare industries.
Meta Learning
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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
Advances In High Power Lasers For Interdisciplinary Applications
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Author : Shuo Liu
language : en
Publisher: Frontiers Media SA
Release Date : 2023-12-22
Advances In High Power Lasers For Interdisciplinary Applications written by Shuo Liu and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-22 with Science categories.
Automated Machine Learning
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Author : Frank Hutter
language : en
Publisher: Springer
Release Date : 2019-05-17
Automated Machine Learning written by Frank Hutter and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-17 with Computers categories.
This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.
Contributions Presented At The International Conference On Computing Communication Cybersecurity And Ai July 3 4 2024 London Uk
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Author : Nitin Naik
language : en
Publisher: Springer Nature
Release Date : 2024-12-19
Contributions Presented At The International Conference On Computing Communication Cybersecurity And Ai July 3 4 2024 London Uk written by Nitin Naik and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-19 with Computers categories.
This book offers an in-depth exploration of cutting-edge research across the interconnected fields of computing, communication, cybersecurity, and artificial intelligence. It serves as a comprehensive guide to the technologies shaping our digital world, providing both a profound understanding of these domains and practical strategies for addressing their challenges. The content is drawn from the International Conference on Computing, Communication, Cybersecurity and AI (C3AI 2024), held in London, UK, from July 3 to 4, 2024. The conference attracted 66 submissions from 17 countries, including the USA, UK, Canada, Brazil, India, China, Germany, and Spain. Of these, 47 high-calibre papers were rigorously selected through a meticulous review process, where each paper received three to four reviews to ensure quality and relevance. This book is an essential resource for readers seeking a thorough and timely review of the latest advancements and trends in computing, communication, cybersecurity, and artificial intelligence.
Medical Image Computing And Computer Assisted Intervention Miccai 2021
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Author : Marleen de Bruijne
language : en
Publisher: Springer Nature
Release Date : 2021-09-23
Medical Image Computing And Computer Assisted Intervention Miccai 2021 written by Marleen de Bruijne and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-23 with Computers categories.
The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.* The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging – others; and clinical applications - oncology Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound *The conference was held virtually.