Advances in Machine Learning and Image Analysis for GeoAI PDF Download

Author: Saurabh Prasad
Publisher: Elsevier
ISBN: 044319078X
Category : Science
Languages : en
Pages : 366

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Book Description
Advances in Machine Learning and Image Analysis for GeoAI provides state-of-the-art machine learning and signal processing techniques for a comprehensive collection of geospatial sensors and sensing platforms. The book covers supervised, semi-supervised and unsupervised geospatial image analysis, sensor fusion across modalities, image super-resolution, transfer learning across sensors and time-points, and spectral unmixing among other topics. The chapters in these thematic areas cover a variety of algorithmic frameworks such as variants of convolutional neural networks, graph convolutional networks, multi-stream networks, Bayesian networks, generative adversarial networks, transformers and more.Advances in Machine Learning and Image Analysis for GeoAI provides graduate students, researchers and practitioners in the area of signal processing and geospatial image analysis with the latest techniques to implement deep learning strategies in their research. - Covers the latest machine learning and signal processing techniques that can effectively leverage multimodal geospatial imagery at scale - Chapters cover a variety of algorithmic frameworks pertaining to GeoAI, including superresolution, self-supervised learning, data fusion, explainable AI, among others - Presents cutting-edge deep learning architectures optimized for a wide array of geospatial imagery

Author: Stan Openshaw
Publisher: John Wiley & Sons
ISBN:
Category : Computers
Languages : en
Pages : 356

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Book Description
This unique work introduces the basic principles of artificial intelligence with applications in geographical teaching and research, GIS, and planning. Written in an accessible, non-technical and witty style, this book marks the beginning of the Al revolution in geography with major implications for teaching and research. The authors provide an easy to understand basic introduction to Al relevant to geography. There are no special mathematical and statistical skills needed, indeed these might well be a hindrance. Al is a different way of looking at the world and it requires a willingness to experiment, and readers who are unhindered by the baggage of obsolete technologies and outmoded philosophies of science will probably do best. The text provides an introduction to expert systems, neural nets, genetic algorithms, smart systems and artificial life and shows how they are likely to transform geographical enquiry. A major methodological milestone in geography The first geographical book on artificial intelligence (Al) No need for previous mathematical or statistical skills/knowledge Accessible style makes a difficult subject available to a wide audience Stan Openshaw is one of the world? s leading researchers into geographical computing, spatial analysis and GIS.

Author: Song Gao
Publisher: CRC Press
ISBN: 1003814956
Category : Technology & Engineering
Languages : en
Pages : 508

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Book Description
This comprehensive handbook covers Geospatial Artificial Intelligence (GeoAI), which is the integration of geospatial studies and AI machine (deep) learning and knowledge graph technologies. It explains key fundamental concepts, methods, models, and technologies of GeoAI, and discusses the recent advances, research tools, and applications that range from environmental observation and social sensing to natural disaster responses. As the first single volume on this fast-emerging domain, Handbook of Geospatial Artificial Intelligence is an excellent resource for educators, students, researchers, and practitioners utilizing GeoAI in fields such as information science, environment and natural resources, geosciences, and geography. Features Provides systematic introductions and discussions of GeoAI theory, methods, technologies, applications, and future perspectives Covers a wide range of GeoAI applications and case studies in practice Offers supplementary materials such as data, programming code, tools, and case studies Discusses the recent developments of GeoAI methods and tools Includes contributions written by top experts in cutting-edge GeoAI topics This book is intended for upper-level undergraduate and graduate students from different disciplines and those taking GIS courses in geography or computer sciences as well as software engineers, geospatial industry engineers, GIS professionals in non-governmental organizations, and federal/state agencies who use GIS and want to learn more about GeoAI advances and applications.

Author: Gian Luca Foresti
Publisher: Springer Nature
ISBN: 3031510267
Category : Computers
Languages : en
Pages : 515

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Book Description
The two-volume set LNCS 14365 and 14366 constitutes the papers of workshops hosted by the 22nd International Conference on Image Analysis and Processing, ICIAP 2023, held in Udine, Italy, in September 2023. In total, 72 workshop papers and 10 industrial poster session papers have been accepted for publication. Part II of the set, volume 14366, contains 41 papers from the following workshops:– Medical Imaging Hub:• Artificial Intelligence and Radiomics in Computer-Aided Diagnosis (AIR-CAD)• Multi-Modal Medical Imaging Processing (M3IP)• Federated Learning in Medical Imaging and Vision (FedMed)– Digital Humanities Hub:• Artificial Intelligence for Digital Humanities (AI4DH)• Fine Art Pattern Extraction and Recognition (FAPER)• Pattern Recognition for Cultural Heritage (PatReCH)• Visual Processing of Digital Manuscripts: Workflows, Pipelines, BestPractices (ViDiScript)

Author: Mathew Salvaris
Publisher: Apress
ISBN: 1484236793
Category : Computers
Languages : en
Pages : 298

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Book Description
Get up-to-speed with Microsoft's AI Platform. Learn to innovate and accelerate with open and powerful tools and services that bring artificial intelligence to every data scientist and developer. Artificial Intelligence (AI) is the new normal. Innovations in deep learning algorithms and hardware are happening at a rapid pace. It is no longer a question of should I build AI into my business, but more about where do I begin and how do I get started with AI? Written by expert data scientists at Microsoft, Deep Learning with the Microsoft AI Platform helps you with the how-to of doing deep learning on Azure and leveraging deep learning to create innovative and intelligent solutions. Benefit from guidance on where to begin your AI adventure, and learn how the cloud provides you with all the tools, infrastructure, and services you need to do AI. What You'll Learn Become familiar with the tools, infrastructure, and services available for deep learning on Microsoft Azure such as Azure Machine Learning services and Batch AI Use pre-built AI capabilities (Computer Vision, OCR, gender, emotion, landmark detection, and more) Understand the common deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs) with sample code and understand how the field is evolving Discover the options for training and operationalizing deep learning models on Azure Who This Book Is For Professional data scientists who are interested in learning more about deep learning and how to use the Microsoft AI platform. Some experience with Python is helpful.

Author: Gustau Camps-Valls
Publisher: John Wiley & Sons
ISBN: 1119646162
Category : Technology & Engineering
Languages : en
Pages : 436

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Book Description
DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered academic curricula and thus has not yet proliferated. Deep Learning for the Earth Sciences delivers a unique perspective and treatment of the concepts, skills, and practices necessary to quickly become familiar with the application of deep learning techniques to the Earth sciences. The book prepares readers to be ready to use the technologies and principles described in their own research. The distinguished editors have also included resources that explain and provide new ideas and recommendations for new research especially useful to those involved in advanced research education or those seeking PhD thesis orientations. Readers will also benefit from the inclusion of: An introduction to deep learning for classification purposes, including advances in image segmentation and encoding priors, anomaly detection and target detection, and domain adaptation An exploration of learning representations and unsupervised deep learning, including deep learning image fusion, image retrieval, and matching and co-registration Practical discussions of regression, fitting, parameter retrieval, forecasting and interpolation An examination of physics-aware deep learning models, including emulation of complex codes and model parametrizations Perfect for PhD students and researchers in the fields of geosciences, image processing, remote sensing, electrical engineering and computer science, and machine learning, Deep Learning for the Earth Sciences will also earn a place in the libraries of machine learning and pattern recognition researchers, engineers, and scientists.

Author: Pravat Kumar Shit
Publisher: Elsevier
ISBN: 0128230983
Category : Nature
Languages : en
Pages : 478

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Book Description
Forest Resources Resilience and Conflicts presents modern remote sensing and GIS techniques for Sustainable Livelihood. It provides an up-to-date critical analysis of the discourse surrounding forest resources and society, illustrating the relationship between forest resources and the livelihood of local people. The book is organized into four parts consisting of 31 chapters. Each chapter then reviews current understanding, present research, and future implications. Utilizing case studies and novel advances in geospatial technologies, Forest Resources Resilience and Conflicts provides a timely synthesis of a rapidly growing field and stimulates ideas for future work, especially considering sustainable development goals.In addition, the book presents the effective contribution of the forestry sector to populations' livelihoods through improved collection of forestry statistics that foster the understanding and integration of the forestry sector in poverty reduction processes and the national economy to enhance its integration in national planning. It is a valuable resource for researchers and students in environmental science, especially those interested in forestry, geography, and remote sensing. - Demonstrates tools and techniques for measurement, monitoring, mapping, and modeling of forest resources - Explores state-of-the-art techniques using open source software, statistical programming, and GIS, focusing on recent trends in data mining and machine learning - Addresses a wide range of issues with both environmental and societal implications - Provides a global review of the multiple roles of forest resources utilizing case studies to illustrate management strategies and techniques

Author: Padmesh Tripathi
Publisher: John Wiley & Sons
ISBN: 1394200714
Category : Computers
Languages : en
Pages : 373

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Book Description
This book gives comprehensive insights into the application of AI, machine learning, and deep learning in developing efficient and optimal surveillance systems for both indoor and outdoor environments, addressing the evolving security challenges in public and private spaces. Mathematical Models Using Artificial Intelligence for Surveillance Systems aims to collect and publish basic principles, algorithms, protocols, developing trends, and security challenges and their solutions for various indoor and outdoor surveillance applications using artificial intelligence (AI). The book addresses how AI technologies such as machine learning (ML), deep learning (DL), sensors, and other wireless devices could play a vital role in assisting various security agencies. Security and safety are the major concerns for public and private places in every country. Some places need indoor surveillance, some need outdoor surveillance, and, in some places, both are needed. The goal of this book is to provide an efficient and optimal surveillance system using AI, ML, and DL-based image processing. The blend of machine vision technology and AI provides a more efficient surveillance system compared to traditional systems. Leading scholars and industry practitioners are expected to make significant contributions to the chapters. Their deep conversations and knowledge, which are based on references and research, will result in a wonderful book and a valuable source of information.

Author: Sergio J. Rey
Publisher: Edward Elgar Publishing
ISBN: 1789903947
Category : Technology & Engineering
Languages : en
Pages : 589

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Book Description
Providing an authoritative assessment of the current landscape of spatial analysis in the social sciences, this cutting-edge Handbook covers the full range of standard and emerging methods across the social science domain areas in which these methods are typically applied. Accessible and comprehensive, it expertly answers the key questions regarding the dynamic intersection of spatial analysis and the social sciences.

Author: Yosoon Choi
Publisher: MDPI
ISBN: 3039364898
Category : Science
Languages : en
Pages : 264

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Book Description
Geographic information systems (GISs) have played a vital role in Earth sciences by providing a powerful means of observing the world and various tools for solving complex problems. The scientific community has used GISs to reveal fascinating details about the Earth and other planets. This book on recent advances in GIS for Earth sciences includes 12 publications from esteemed research groups worldwide. The research and review papers in this book belong to the following broad categories: Earth science informatics (geoinformatics), mining, hydrology, natural hazards, and society.