Artificial Intelligence And Computer Vision For Ecological Informatics

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Artificial Intelligence And Computer Vision Technologies For Ecological Informatics

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Author : Siddharth Singh Chouhan
language : en
Publisher:
Release Date : 2025-08-27

Artificial Intelligence And Computer Vision Technologies For Ecological Informatics written by Siddharth Singh Chouhan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-27 with Computers categories.

This book explores AI, machine learning, deep learning, bio-inspired algorithms, and computer vision in ecological informatics. It covers remote sensing, water body evaluation, agriculture mapping, aquatic monitoring and terrestrial ecosystems. It provides insights to develop models and prototypes benefiting society and the environment.

Artificial Intelligence And Computer Vision For Ecological Informatics

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Author : Siddharth Singh Chouhan
language : en
Publisher: CRC Press
Release Date : 2025-08-27

Artificial Intelligence And Computer Vision For Ecological Informatics written by Siddharth Singh Chouhan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-27 with Technology & Engineering categories.

Ecological informatics, more commonly known as Ecoinformatics, is the study of environmental sciences and ecological information. It is an emerging interdisciplinary framework for the management, analysis, and synthesis of ecological data with the help of advanced computational intelligence algorithms. Management in this context is data acquisition, preprocessing, and sharing the data. Analysis and synthesis are the process of extracting useful information and forecasting with the help of intelligent algorithms. The aim of this book is to encapsulate concepts and theories of artificial intelligence and computer vision algorithms used for the evaluation of various ecological informatics applications. It focuses on soft computing, machine learning, deep learning, artificial intelligence, bio-inspired algorithms, data analysis tools, data visualization tools, and computer vision algorithms used in ecological informatics. The book covers remote sensing applications, water bodies evaluation, agriculture mapping, aquatic mapping, forest management, and terrestrial ecosystems. The book will be useful to students, researchers, scientists, and field experts in directing their work towards this domain, to deliver and design models and prototypes for the benefit of society and the environment.

Computer Vision And Pattern Recognition In Environmental Informatics

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Author : Zhou, Jun
language : en
Publisher: IGI Global
Release Date : 2015-10-19

Computer Vision And Pattern Recognition In Environmental Informatics written by Zhou, Jun and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-19 with Technology & Engineering categories.

Computer Vision and Pattern Recognition (CVPR) together play an important role in the processes involved in environmental informatics due to their pervasive, non-destructive, effective, and efficient natures. As a result, CVPR has made significant contributions to the field of environmental informatics by enabling multi-modal data fusion and feature extraction, supporting fast and reliable object detection and classification, and mining the intrinsic relationship between different aspects of environmental data. Computer Vision and Pattern Recognition in Environmental Informatics describes a number of methods and tools for image interpretation and analysis, which enables observation, modelling, and understanding of environmental targets. In addition to case studies on monitoring and modeling plant, soil, insect, and aquatic animals, this publication includes discussions on innovative new ideas related to environmental monitoring, automatic fish segmentation and recognition, real-time motion tracking systems, sparse coding and decision fusion, and cell phone image-based classification and provides useful references for professionals, researchers, engineers, and students with various backgrounds within a multitude of communities.

Ecological Informatics

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Author : Friedrich Recknagel
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-12-11

Ecological Informatics written by Friedrich Recknagel and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-12-11 with Science categories.

Ecological Informatics is defined as the design and application of computational techniques for ecological analysis, synthesis, forecasting and management. The book provides an introduction to the scope, concepts and techniques of this newly emerging discipline. It illustrates numerous applications of Ecological Informatics for stream systems, river systems, freshwater lakes and marine systems as well as image recognition at micro and macro scale. Case studies focus on applications of artificial neural networks, genetic algorithms, fuzzy logic and adaptive agents to current ecological management issues such as toxic algal blooms, eutrophication, habitat degradation, conservation of biodiversity and sustainable fishery.

Reshaping Environmental Science Through Machine Learning And Iot

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Author : Gupta, Rajeev Kumar
language : en
Publisher: IGI Global
Release Date : 2024-05-06

Reshaping Environmental Science Through Machine Learning And Iot written by Gupta, Rajeev Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-06 with Technology & Engineering categories.

In the face of escalating environmental challenges such as climate change, air and water pollution, and natural disasters, traditional approaches to understanding and addressing these issues have yet to be proven sufficient. Academic scholars are compelled to seek innovative solutions that marry digital intelligence and natural ecosystems. Reshaping Environmental Science Through Machine Learning and IoT serves as a comprehensive exploration into the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) to address critical environmental challenges. The book establishes a robust foundation in ML and IoT, explaining their relevance to environmental science. As the narrative unfolds, it delves into diverse applications, providing theoretical insights alongside practical knowledge. From interpreting weather patterns to predicting air and water quality, the book navigates through the intricate web of environmental complexities. Notably, it unveils approaches to disaster management, waste sorting, and climate change monitoring, showcasing the symbiotic relationship between digital intelligence and natural ecosystems. This book is ideal for audiences from students and researchers to data scientists and disaster management professionals with a nuanced understanding of IoT, ML, and Artificial Intelligence (AI).

Artificial Intelligence Applications In Specialty Crops

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Author : Yiannis Ampatzidis
language : en
Publisher: Frontiers Media SA
Release Date : 2022-03-02

Artificial Intelligence Applications In Specialty Crops written by Yiannis Ampatzidis 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 2022-03-02 with Science categories.

Factoring Technology In Global Sustainability

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Author : Wasswa Shafik
language : en
Publisher: Springer Nature
Release Date : 2025-06-11

Factoring Technology In Global Sustainability written by Wasswa Shafik and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-11 with Business & Economics categories.

This book explores the critical role of technology in advancing the United Nations' 2030 Agenda for Sustainable Development. With the world facing pressing challenges like climate change, poverty, and environmental degradation, innovations such as artificial intelligence, big data, the Internet of Things, blockchain, and renewable energy are increasingly shaping global efforts to achieve the Sustainable Development Goals (SDGs). The book examines how these technologies are transforming key sectors, from agriculture and healthcare to energy and education, offering practical solutions to complex global problems. By focusing on each SDG, it provides a thorough look at how technological advancements are being applied to drive sustainable development. Through real-world case studies, the book discusses the practical challenges of scaling and financing these technologies while highlighting the importance of governance, policy, and international cooperation in their success. It also explores how governments, businesses, and global institutions can leverage these innovations to build more resilient and inclusive societies. This book is intended for scholars, policymakers, entrepreneurs, and professionals in sustainability who are seeking a deeper understanding of how technology can be integrated into strategies for achieving the SDGs. As the 2030 deadline approaches, it also offers insights into future trends and emerging technologies that will shape a more sustainable and equitable world in the years to come.

Global Sustainable Transition With Inclusion

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Author : Wasswa Shafik
language : en
Publisher: Springer Nature
Release Date : 2025-06-16

Global Sustainable Transition With Inclusion written by Wasswa Shafik and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-16 with Business & Economics categories.

This book provides a comprehensive exploration of inclusive, sustainable development, emphasizing the critical need to integrate the perspectives and needs of people with disabilities and marginalized communities into the global sustainability transition to a sustainable future. Through highlighting the intersectionality of identity and the unique challenges faced by these groups, the book addresses a pressing issue: the often-overlooked barriers that hinder their full participation in sustainable transitions. Organized into three parts, the book first contextualizes the relationship between sustainability and inclusion. It delves into the historical and theoretical frameworks that shape our understanding of marginalization, exploring how disability intersects with various social identities. This foundation sets the stage for an in-depth analysis of the United Nations Sustainable Development Goals (SDGs) and the ways in which they can be made more inclusive, ensuring that no one is left behind. The second part identifies and examines the myriad barriers to inclusion within sustainable practices. It addresses structural, socioeconomic, and cultural obstacles that perpetuate exclusion while also critiquing existing policy frameworks for their limitations in addressing the needs of marginalized populations. Through case studies, the book highlights successful initiatives and innovative practices that promote accessibility and equity, mainly through the use of assistive technologies and community engagement. In the final section, the book outlines actionable strategies for fostering inclusive, sustainable development. It emphasizes the importance of community engagement, participatory decision-making, and the empowerment of marginalized voices. Additionally, it discusses metrics for monitoring and evaluating the impact of sustainability initiatives on people with disabilities, providing a framework for accountability and continuous improvement. This book aims to bridge the gap between sustainability and social justice, offering a roadmap for stakeholders, policymakers, and practitioners committed to creating a more inclusive world. This book targets academics, policymakers, non-profit societies, and activists working at the intersection of sustainability and social equity and serves as a vital resource for those seeking to understand and promote inclusive practices in the global sustainable transition.

Covariances In Computer Vision And Machine Learning

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Author : Hà Quang Minh
language : en
Publisher: Springer Nature
Release Date : 2022-05-31

Covariances In Computer Vision And Machine Learning written by Hà Quang Minh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.

Covariance matrices play important roles in many areas of mathematics, statistics, and machine learning, as well as their applications. In computer vision and image processing, they give rise to a powerful data representation, namely the covariance descriptor, with numerous practical applications. In this book, we begin by presenting an overview of the {\it finite-dimensional covariance matrix} representation approach of images, along with its statistical interpretation. In particular, we discuss the various distances and divergences that arise from the intrinsic geometrical structures of the set of Symmetric Positive Definite (SPD) matrices, namely Riemannian manifold and convex cone structures. Computationally, we focus on kernel methods on covariance matrices, especially using the Log-Euclidean distance. We then show some of the latest developments in the generalization of the finite-dimensional covariance matrix representation to the {\it infinite-dimensional covariance operator} representation via positive definite kernels. We present the generalization of the affine-invariant Riemannian metric and the Log-Hilbert-Schmidt metric, which generalizes the Log-Euclidean distance. Computationally, we focus on kernel methods on covariance operators, especially using the Log-Hilbert-Schmidt distance. Specifically, we present a two-layer kernel machine, using the Log-Hilbert-Schmidt distance and its finite-dimensional approximation, which reduces the computational complexity of the exact formulation while largely preserving its capability. Theoretical analysis shows that, mathematically, the approximate Log-Hilbert-Schmidt distance should be preferred over the approximate Log-Hilbert-Schmidt inner product and, computationally, it should be preferred over the approximate affine-invariant Riemannian distance. Numerical experiments on image classification demonstrate significant improvements of the infinite-dimensional formulation over the finite-dimensional counterpart. Given the numerous applications of covariance matrices in many areas of mathematics, statistics, and machine learning, just to name a few, we expect that the infinite-dimensional covariance operator formulation presented here will have many more applications beyond those in computer vision.

Intelligent Systems And Applications In Computer Vision

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Author : Nitin Mittal
language : en
Publisher: CRC Press
Release Date : 2023-11-02

Intelligent Systems And Applications In Computer Vision written by Nitin Mittal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-02 with Computers categories.

The book comprehensively covers a wide range of evolutionary computer vision methods and applications, feature selection and extraction for training and classification, and metaheuristic algorithms in image processing. It further discusses optimized image segmentation, its analysis, pattern recognition, and object detection. Features: Discusses machine learning-based analytics such as GAN networks, autoencoders, computational imaging, and quantum computing Covers deep learning algorithms in computer vision Showcases novel solutions such as multi-resolution analysis in imaging processing, and metaheuristic algorithms for tackling challenges associated with image processing Highlight optimization problems such as image segmentation and minimized feature design vector Presents platform and simulation tools for image processing and segmentation The book aims to get the readers familiar with the fundamentals of computational intelligence as well as the recent advancements in related technologies like smart applications of digital images, and other enabling technologies from the context of image processing and computer vision. It further covers important topics such as image watermarking, steganography, morphological processing, and optimized image segmentation. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in fields including electrical engineering, electronics, communications engineering, and computer engineering.