Optics and Machine Vision for Marine Observation PDF Download

Author: Hong Song
Publisher: Frontiers Media SA
ISBN: 2832533299
Category : Science
Languages : en
Pages : 324

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Author: Haiyong Zheng
Publisher: Frontiers Media SA
ISBN: 2832549055
Category : Science
Languages : en
Pages : 555

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Book Description
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.

Author: Oscar Pizarro
Publisher: Frontiers Media SA
ISBN: 288971084X
Category : Science
Languages : en
Pages : 235

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Author: Ni-Bin Chang
Publisher: CRC Press
ISBN: 1498774342
Category : Technology & Engineering
Languages : en
Pages : 508

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In the last few years the scientific community has realized that obtaining a better understanding of interactions between natural systems and the man-made environment across different scales demands more research efforts in remote sensing. An integrated Earth system observatory that merges surface-based, air-borne, space-borne, and even underground sensors with comprehensive and predictive capabilities indicates promise for revolutionizing the study of global water, energy, and carbon cycles as well as land use and land cover changes. The aim of this book is to present a suite of relevant concepts, tools, and methods of integrated multisensor data fusion and machine learning technologies to promote environmental sustainability. The process of machine learning for intelligent feature extraction consists of regular, deep, and fast learning algorithms. The niche for integrating data fusion and machine learning for remote sensing rests upon the creation of a new scientific architecture in remote sensing science that is designed to support numerical as well as symbolic feature extraction managed by several cognitively oriented machine learning tasks at finer scales. By grouping a suite of satellites with similar nature in platform design, data merging may come to help for cloudy pixel reconstruction over the space domain or concatenation of time series images over the time domain, or even both simultaneously. Organized in 5 parts, from Fundamental Principles of Remote Sensing; Feature Extraction for Remote Sensing; Image and Data Fusion for Remote Sensing; Integrated Data Merging, Data Reconstruction, Data Fusion, and Machine Learning; to Remote Sensing for Environmental Decision Analysis, the book will be a useful reference for graduate students, academic scholars, and working professionals who are involved in the study of Earth systems and the environment for a sustainable future. The new knowledge in this book can be applied successfully in many areas of environmental science and engineering.

Author: Han Zhongzhi
Publisher: CRC Press
ISBN: 1000691616
Category : Technology & Engineering
Languages : en
Pages : 349

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In recent years, computer vision is a fast-growing technique of agricultural engineering, especially in quality detection of agricultural products and food safety testing. It can provide objective, rapid, non-contact and non-destructive methods by extracting quantitative information from digital images. Significant scientific and technological advances have been made in quality inspection, classification and evaluation of a wide range of food and agricultural products. Computer Vision-Based Agriculture Engineering focuses on these advances. The book contains 25 chapters covering computer vision, image processing, hyperspectral imaging and other related technologies in peanut aflatoxin, peanut and corn quality varieties, and carrot and potato quality, as well as pest and disease detection. Features: Discusses various detection methods in a variety of agricultural crops Each chapter includes materials and methods used, results and analysis, and discussion with conclusions Covers basic theory, technical methods and engineering cases Provides comprehensive coverage on methods of variety identification, quality detection and detection of key indicators of agricultural products safety Presents information on technology of artificial intelligence including deep learning and transfer learning Computer Vision-Based Agriculture Engineering is a summary of the author's work over the past 10 years. Professor Han has presented his most recent research results in all 25 chapters of this book. This unique work provides students, engineers and technologists working in research, development, and operations in agricultural engineering with critical, comprehensive and readily accessible information. It applies development of artificial intelligence theory and methods including depth learning and transfer learning to the field of agricultural engineering testing.

Author: Md Atiqur Rahman Ahad
Publisher: CRC Press
ISBN: 104002937X
Category : Computers
Languages : en
Pages : 359

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Book Description
Computer vision has made enormous progress in recent years, and its applications are multifaceted and growing quickly, while many challenges still remain. This book brings together a range of leading researchers to examine a wide variety of research directions, challenges, and prospects for computer vision and its applications. This book highlights various core challenges as well as solutions by leading researchers in the field. It covers such important topics as data-driven AI, biometrics, digital forensics, healthcare, robotics, entertainment and XR, autonomous driving, sports analytics, and neuromorphic computing, covering both academic and industry R&D perspectives. Providing a mix of breadth and depth, this book will have an impact across the fields of computer vision, imaging, and AI. Computer Vision: Challenges, Trends, and Opportunities covers timely and important aspects of computer vision and its applications, highlighting the challenges ahead and providing a range of perspectives from top researchers around the world. A substantial compilation of ideas and state-of-the-art solutions, it will be of great benefit to students, researchers, and industry practitioners.

Author: Yingping Li
Publisher: John Wiley & Sons
ISBN: 1119521793
Category : Science
Languages : en
Pages : 324

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A comprehensive handbook on state-of-the-art DAS technology and applications Distributed Acoustic Sensing (DAS) is a technology that records sound and vibration signals along a fiber optic cable. Its advantages of high resolution, continuous, and real-time measurements mean that DAS systems have been rapidly adopted for a range of applications, including hazard mitigation, energy industries, geohydrology, environmental monitoring, and civil engineering. Distributed Acoustic Sensing in Geophysics: Methods and Applications presents experiences from both industry and academia on using DAS in a range of geophysical applications. Volume highlights include: DAS concepts, principles, and measurements Comprehensive review of the historical development of DAS and related technologies DAS applications in hydrocarbon, geothermal, and mining industries DAS applications in seismology DAS applications in environmental and shallow geophysics The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.

Author: Costas A. Varotsos
Publisher: Springer Nature
ISBN: 3031288777
Category : Science
Languages : en
Pages : 531

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This book presents results of the combined use of microwave remote sensing, optical tools, and ecoinformatics methods under solution-applied tasks at both regional and global scales. Ecoinformatics methods are used to assess links between global climate change and the level of ocean pollution, with specific focus on the Arctic Ocean, the Sea of Okhotsk, and the South-China Sea. The theoretical and applied aspects of instrumental tools are considered in this book as a basis for the monitoring of water quality in various watersheds, with particular attention to microwave remote sensing monitoring data to determine the ecotoxicological status of hydro-ecosystems affected by climate change. The book develops new information technologies that provide solutions for hydrochemical tasks using algorithms and models based on computer technologies for big data processing. This will help to synthesize effective computer-based systems for the solution of problems arising due to anthropogenic impacts on hydrological processes and objects at various spatial scales. This book is intended for specialists in the fields of environmental monitoring, climate change, human-nature interactions, and geopolitics. The book will be useful for undergraduate and postgraduate students studying these fields of science as well.

Author: Shuai Liu
Publisher: Springer Nature
ISBN: 3030945510
Category : Computers
Languages : en
Pages : 753

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This two-volume set constitutes the post-conference proceedings of the 5th EAI International Conference on Advanced Hybrid Information Processing, ADHIP 2021, held in October 2021. Due to COVID-19 the conference was held virtually. The 94 papers presented were selected from 254 submissions and focus on theory and application of hybrid information processing technology for smarter and more effective research and application. The theme of ADHIP 2020 was “Social hybrid data processing”. The papers are named in topical sections as follows: Intelligent algorithms in complex environment; AI system research and model design; Method research on Internet of Things technology; Research and analysis with intelligent education.

Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 936

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