Download or read book Deep Learning for Marine Science written by Haiyong Zheng and published by Frontiers Media SA. This book was released on 2024-05-15 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning (DL), mainly composed of deep and complex neural networks such as recurrent network and convolutional network, is an emerging research branch in the field of artificial intelligence and machine learning. DL revolution has a far-reaching impact on all scientific disciplines and every corner of our lives. With continuing technological advances, marine science is entering into the big data era with the exponential growth of information. DL is an effective means of harnessing the power of big data. Combined with unprecedented data from cameras, acoustic recorders, satellite remote sensing, and large model outputs, DL enables scientists to solve complex problems in biology, ecosystems, climate, energy, as well as physical and chemical interactions. Although DL has made great strides, it is still only beginning to emerge in many fields of marine science, especially towards representative applications and best practices for the automatic analysis of marine organisms and marine environments. DL in nowadays' marine science mainly leverages cutting-edge techniques of deep neural networks and massive data which collected by in-situ optical or acoustic imaging sensors for underwater applications, such as plankton classification and coral reef detection. This research topic aims to expand the applications of marine science to cover all aspects of detection, classification, segmentation, localization, and density estimation of marine objects, organisms, and phenomena.
Download or read book Artificial Intelligence Oceanography written by Xiaofeng Li and published by Springer Nature. This book was released on 2023-02-03 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book invites readers to learn how to develop artificial intelligence (AI)-based algorithms to perform their research in oceanography. Various examples are exhibited to guide details of how to feed the big ocean data into the AI models to analyze and achieve optimized results. The number of scholars engaged in AI oceanography research will increase exponentially in the next decade. Therefore, this book will serve as a benchmark providing insights for scholars and graduate students interested in oceanography, computer science, and remote sensing.
Download or read book Fish4Knowledge Collecting and Analyzing Massive Coral Reef Fish Video Data written by Robert B. Fisher and published by Springer. This book was released on 2016-04-04 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a start-to-finish overview of the whole Fish4Knowledge project, in 18 short chapters, each describing one aspect of the project. The Fish4Knowledge project explored the possibilities of big video data, in this case from undersea video. Recording and analyzing 90 thousand hours of video from ten camera locations, the project gives a 3 year view of fish abundance in several tropical coral reefs off the coast of Taiwan. The research system built a remote recording network, over 100 Tb of storage, supercomputer processing, video target detection and tracking, fish species recognition and analysis, a large SQL database to record the results and an efficient retrieval mechanism. Novel user interface mechanisms were developed to provide easy access for marine ecologists, who wanted to explore the dataset. The book is a useful resource for system builders, as it gives an overview of the many new methods that were created to build the Fish4Knowledge system in a manner that also allows readers to see how all the components fit together.
Download or read book Machine Learning to Improve Marine Science for the Sustainability of Living Ocean Resources written by William L. Michaels and published by . This book was released on 2019 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Machine Learning Methods in the Environmental Sciences written by William W. Hsieh and published by Cambridge University Press. This book was released on 2009-07-30 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: A graduate textbook that provides a unified treatment of machine learning methods and their applications in the environmental sciences.
Download or read book Spatiotemporal Modeling and Analysis in Marine Science written by Junyu He and published by Frontiers Media SA. This book was released on 2023-11-29 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the development of earth observation technologies (such as satellite remote sensing, unmanned aerial vehicle, autonomous underwater vehicle, etc.), an era of big data with important and non-negligible spatial/temporal attributes comes. Novel and rigorous spatiotemporal methodologies and models are needed to process and analyze marine big data. Since many marine environmental processes, such as pollutants diffusion, algae distributions etc., vary or evolve across spatiotemporal domains, detecting the distributions and patterns of marine fauna and, particularly in the coastal regions, will improve our understanding of marine systems and can be beneficial in marine environmental management. The goals of this Research Topic, therefore, are two-fold: (a) to develop methodologies and models in theory and applications, including spatiotemporal geostatistics, geographic information system, deep learning, etc.; (b) to quantitatively gain the knowledge of the marine environment. This Research Topic will provide a platform for researchers to share and exchange their new knowledge gained in a spatiotemporal domain of marine or coastal regions. This Research Topic will cover, but is not limited to, the following areas: • Spatiotemporal variations of physical/chemical/biological indicators (such as chlorophyll, temperature, salinity, colorful dissolved organic matter, suspended solids, nutrients, microplastic, etc.) in marine. • Spatiotemporal variations of potential fishing grounds in marine. • Spatiotemporal variations of the ecosystems in coastal regions, such as salt marshes, mangroves, seagrass, macroalgae, etc. • Spatiotemporal distributions of the pollutants (such as heavy metals, polycyclic aromatic hydrocarbon, etc.) in marine and sediments. • Spatiotemporal evolution pattern modeling and prediction of the marine disasters and abnormal phenomena (such as algal bloom, typhoons, SST anomalies, etc).
Download or read book Deep Learning Algorithms and Applications written by Witold Pedrycz and published by Springer. This book was released on 2019-11-04 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent alignment with the essential characteristics of the nature of learning encountered in the practical problems being tackled. Intended for readers interested in acquiring practical knowledge of analysis, design, and deployment of deep learning solutions to real-world problems, it covers a wide range of the paradigm’s algorithms and their applications in diverse areas including imaging, seismic tomography, smart grids, surveillance and security, and health care, among others. Featuring systematic and comprehensive discussions on the development processes, their evaluation, and relevance, the book offers insights into fundamental design strategies for algorithms of deep learning.
Download or read book Handbook of Fish Biology and Fisheries written by Paul J. B. Hart and published by John Wiley & Sons. This book was released on 2008-04-15 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent decades have witnessed strong declines in fish stocks aroundthe globe, amid growing concerns about the impact of fisheries onmarine and freshwater biodiversity. Fisheries biologists andmanagers are therefore increasingly asking about aspects ofecology, behaviour, evolution and biodiversity that weretraditionally studied by people working in very separate fields.This has highlighted the need to work more closely together, inorder to help ensure future success both in management andconservation. The Handbook of Fish Biology and Fisheries has beenwritten by an international team of scientists and practitioners,to provide an overview of the biology of freshwater and marine fishspecies together with the science that supports fisheriesmanagement and conservation. This volume, subtitled Fish Biology, reviews a broadvariety of topics from evolutionary relationships and globalbiogeography to physiology, recruitment, life histories, genetics,foraging behaviour, reproductive behaviour and community ecology.The second volume, subtitled Fisheries, uses much of thisinformation in a wide-ranging review of fisheries biology,including methods of capture, marketing, economics, stockassessment, forecasting, ecosystem impacts and conservation. Together, these books present the state of the art in ourunderstanding of fish biology and fisheries and will serve asvaluable references for undergraduates and graduates looking for acomprehensive source on a wide variety of topics in fisheriesscience. They will also be useful to researchers who needup-to-date reviews of topics that impinge on their fields, anddecision makers who need to appreciate the scientific backgroundfor management and conservation of aquatic ecosystems. To order volume I, go to the box in the top right hand corner.Alternatively to order volume II, go to:http://www.blackwellpublishing.com/book.asp?ref=063206482X or toorder the 2 volume set, go to:http://www.blackwellpublishing.com/book.asp?ref=0632064838. Provides a unique overview of the study of fish biology andecology, and the assessment and management of fish populations andecosystems. The first volume concentrates on aspects of fish biology andecology, both at the individual and population levels, whilst thesecond volume addresses the assessment and management of fishpopulations and ecosystems. Written by an international team of expert scientists andpractitioners. An invaluable reference tool for both students, researchers andpractitioners working in the fields of fish biology andfisheries.
Download or read book Handbook of Deep Learning Applications written by Valentina Emilia Balas and published by Springer. This book was released on 2019-03-06 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.
Download or read book Exploring Creation with Marine Biology written by Sherri Seligson and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apologia’s Marine Biology course is one of the few homeschool science courses that include an entire education on ecology. It gives students self-directed learning tools to ensure that they thrive and master key science concepts. God designed the earth’s intricate ecosystem for his glory and the needs of those He created, and it is crucial for Christians in our day to accurately understand the ocean’s ecosystems and resources and how we can best steward them.--Publisher
Download or read book Exemplary Practices in Marine Science Education written by Géraldine Fauville and published by Springer. This book was released on 2018-06-28 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume is the premier book dedicated exclusively to marine science education and improving ocean literacy, aiming to showcase exemplary practices in marine science education and educational research in this field on a global scale. It informs, inspires, and provides an intellectual forum for practitioners and researchers in this particular context. Subject areas include sections on marine science education in formal, informal and community settings. This book will be useful to marine science education practitioners (e.g. formal and informal educators) and researchers (both education and science).
Download or read book Marine Big Data written by Dongmei Huang and published by World Scientific Publishing Company. This book was released on 2019 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the volume of marine big data has increased dramatically, one of the main concerns is how to fully exploit the value of such data in the development of marine economy and marine science and technology. The book covers data acquisition, feature classification, processing and applications of marine big data in evaluation and decision-making, using case studies such as storm surge and marine oil spill disaster.
Download or read book Shape Contour and Grouping in Computer Vision written by David A. Forsyth and published by Springer Science & Business Media. This book was released on 1999-11-03 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision has been successful in several important applications recently. Vision techniques can now be used to build very good models of buildings from pictures quickly and easily, to overlay operation planning data on a neuros- geon’s view of a patient, and to recognise some of the gestures a user makes to a computer. Object recognition remains a very di cult problem, however. The key questions to understand in recognition seem to be: (1) how objects should be represented and (2) how to manage the line of reasoning that stretches from image data to object identity. An important part of the process of recognition { perhaps, almost all of it { involves assembling bits of image information into helpful groups. There is a wide variety of possible criteria by which these groups could be established { a set of edge points that has a symmetry could be one useful group; others might be a collection of pixels shaded in a particular way, or a set of pixels with coherent colour or texture. Discussing this process of grouping requires a detailed understanding of the relationship between what is seen in the image and what is actually out there in the world.
Download or read book Deep Learning for Hydrometeorology and Environmental Science written by Taesam Lee and published by Springer Nature. This book was released on 2021-01-27 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a step-by-step methodology and derivation of deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN), especially for estimating parameters, with back-propagation as well as examples with real datasets of hydrometeorology (e.g. streamflow and temperature) and environmental science (e.g. water quality). Deep learning is known as part of machine learning methodology based on the artificial neural network. Increasing data availability and computing power enhance applications of deep learning to hydrometeorological and environmental fields. However, books that specifically focus on applications to these fields are limited. Most of deep learning books demonstrate theoretical backgrounds and mathematics. However, examples with real data and step-by-step explanations to understand the algorithms in hydrometeorology and environmental science are very rare. This book focuses on the explanation of deep learning techniques and their applications to hydrometeorological and environmental studies with real hydrological and environmental data. This book covers the major deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN) as well as the conventional artificial neural network model.
Download or read book Optics and Machine Vision for Marine Observation written by Hong Song and published by Frontiers Media SA. This book was released on 2023-10-13 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Artificial Intelligence Methods in the Environmental Sciences written by Sue Ellen Haupt and published by Springer Science & Business Media. This book was released on 2008-11-28 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.
Download or read book Machine Learning for Ecology and Sustainable Natural Resource Management written by Grant Humphries and published by Springer. This book was released on 2018-11-05 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ecologists and natural resource managers are charged with making complex management decisions in the face of a rapidly changing environment resulting from climate change, energy development, urban sprawl, invasive species and globalization. Advances in Geographic Information System (GIS) technology, digitization, online data availability, historic legacy datasets, remote sensors and the ability to collect data on animal movements via satellite and GPS have given rise to large, highly complex datasets. These datasets could be utilized for making critical management decisions, but are often “messy” and difficult to interpret. Basic artificial intelligence algorithms (i.e., machine learning) are powerful tools that are shaping the world and must be taken advantage of in the life sciences. In ecology, machine learning algorithms are critical to helping resource managers synthesize information to better understand complex ecological systems. Machine Learning has a wide variety of powerful applications, with three general uses that are of particular interest to ecologists: (1) data exploration to gain system knowledge and generate new hypotheses, (2) predicting ecological patterns in space and time, and (3) pattern recognition for ecological sampling. Machine learning can be used to make predictive assessments even when relationships between variables are poorly understood. When traditional techniques fail to capture the relationship between variables, effective use of machine learning can unearth and capture previously unattainable insights into an ecosystem's complexity. Currently, many ecologists do not utilize machine learning as a part of the scientific process. This volume highlights how machine learning techniques can complement the traditional methodologies currently applied in this field.
