Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval, Zhang Dengsheng
Автор: Surekha Borra; Rohit Thanki; Nilanjan Dey Название: Satellite Image Analysis: Clustering and Classification ISBN: 9811364230 ISBN-13(EAN): 9789811364235 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Thanks to recent advances in sensors, communication and satellite technology, data storage, processing and networking capabilities, satellite image acquisition and mining are now on the rise. In turn, satellite images play a vital role in providing essential geographical information. Highly accurate automatic classification and decision support systems can facilitate the efforts of data analysts, reduce human error, and allow the rapid and rigorous analysis of land use and land cover information. Integrating Machine Learning (ML) technology with the human visual psychometric can help meet geologists’ demands for more efficient and higher-quality classification in real time.
This book introduces readers to key concepts, methods and models for satellite image analysis; highlights state-of-the-art classification and clustering techniques; discusses recent developments and remaining challenges; and addresses various applications, making it a valuable asset for engineers, data analysts and researchers in the fields of geographic information systems and remote sensing engineering.
Автор: Binxing Fang, Yan Jia Название: Groups and Interaction ISBN: 3110597772 ISBN-13(EAN): 9783110597776 Издательство: Walter de Gruyter Рейтинг: Цена: 16169.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The three volume set provides a systematic overview of theories and technique on social network analysis.Volume 2 of the set mainly focuses on the formation and interaction of group behaviors. Users’ behavior analysis, sentiment analysis, influence analysis and collective aggregation are discussed in detail as well. It is an essential reference for scientist and professionals in computer science.
Автор: Francesco Mola; Claudio Conversano; Maurizio Vichi Название: Classification, (Big) Data Analysis and Statistical Learning ISBN: 3319557076 ISBN-13(EAN): 9783319557076 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data analytics, time series clustering, integration of data from different sources, as well as social networks. It covers both methodological aspects as well as applications to a wide range of areas such as economics, marketing, education, social sciences, medicine, environmental sciences and the pharmaceutical industry. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field. The peer-reviewed contributions were presented at the 10th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in Santa Margherita di Pula (Cagliari), Italy, October 8–10, 2015.
Автор: Akinori Okada; Tadashi Imaizumi; Hans-Hermann Bock Название: Cooperation in Classification and Data Analysis ISBN: 3642006671 ISBN-13(EAN): 9783642006678 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents theories, models, algorithms, and applications in clustering, classification, and visualization. This work includes applications of clustering, classification, and visualization in various fields such as marketing, recommendation system, biology, sociology, and social survey.
Автор: Gupta S. Dutta, Ibaraki Yasuomi Название: Plant Image Analysis: Fundamentals and Applications ISBN: 1466583010 ISBN-13(EAN): 9781466583016 Издательство: Taylor&Francis Рейтинг: Цена: 27562.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The application of imaging techniques in plant and agricultural sciences had previously been confined to images obtained through remote sensing techniques. Technological advancements now allow image analysis for the nondestructive and objective evaluation of biological objects. This has opened a new window in the field of plant science.
Plant Image Analysis: Fundamentals and Applications introduces the basic concepts of image analysis and discusses various techniques in plant imaging, their applications, and future potential. Several types of imaging techniques are discussed including RGB, hyperspectral, thermal, PRI, chlorophyll fluorescence, ROS, and chromosome imaging. The book also covers the use of these techniques in assessing plant growth, early detection of disease and stress, fruit crop yield, plant chromosome analysis, plant phenotyping, and nutrient status both in vivo and in vitro.
The book is an authoritative guide for researchers and those teaching in the fields of stress physiology, precision agriculture, agricultural biotechnology, and cell and developmental biology. Graduate students and professionals using machine vision in plant science will also benefit from this comprehensive resource.
Автор: Paula Brito; Patrice Bertrand; Guy Cucumel; Franci Название: Selected Contributions in Data Analysis and Classification ISBN: 3540735585 ISBN-13(EAN): 9783540735588 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents methodological developments in data analysis and classification. This work covers topics including, methods for classification and clustering, dissimilarity analysis, graph analysis, consensus methods, conceptual analysis of data, analysis of symbolic data, data mining, and knowledge discovery in databases.
Описание: Showcases an effective methodology for classification and clustering of web sites from a usability point of view. While the clustering and classification is accomplished by using an open source tool, WEKA, the basic dataset for the selected websites has been arrived at by using a free tool site-analyser. As a case study, several commercial websites are analysed.
Автор: Yujin Zhang Название: Image Analysis ISBN: 3110520338 ISBN-13(EAN): 9783110520330 Издательство: Walter de Gruyter Цена: 11148.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This graduate textbook presents fundamentals, applications and evaluation of image segregation, unit description, feature measurement and pattern recognition. Analysis on textile, shape and motion are discussed and mathematical tools are employed extensively. Rich in examples and excises, it prepares electrical engineering and computer science students with knowledge and skills for further studies on image understanding.
Автор: Kumar, Anil , Kumar, A. Senthil , Upadhyay, Priy Название: Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification ISBN: 036735571X ISBN-13(EAN): 9780367355715 Издательство: Taylor&Francis Рейтинг: Цена: 15004.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book covers the state of art image classification methods for discrimination of earth objects from remote sensing satellite data with an emphasis on fuzzy based learning methods including applications for preparing land cover classification outputs from actual satellite data. All algorithms are supported by in-house developed tool as SMIC.
Описание: Explores new developments in the field of information and communication technologies and explores how complex information systems interact with and affect one another, woven into the fabric of an information-rich world. This handbook includes coverage of customer experience management, information systems planning, cellular networking, public policy development, and knowledge governance.
Автор: Dengsheng Zhang Название: Fundamentals of Image Data Mining ISBN: 3030179885 ISBN-13(EAN): 9783030179885 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Поставка под заказ.
Описание: This reader-friendly textbook presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. The coverage spans all aspects of image analysis and understanding, offering deep insights into areas of feature extraction, machine learning, and image retrieval. The theoretical coverage is supported by practical mathematical models and algorithms, utilizing data from real-world examples and experiments.Topics and features: describes the essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transforms; reviews a varied range of state-of-the-art models, algorithms, and procedures for image mining; emphasizes how to deal with real image data for practical image mining; highlights how such features as color, texture, and shape can be mined or extracted from images for image representation; presents four powerful approaches for classifying image data, namely, Bayesian classification, Support Vector Machines, Neural Networks, and Decision Trees; discusses techniques for indexing, image ranking, and image presentation, along with image database visualization methods; provides self-test exercises with instructions or Matlab code, as well as review summaries at the end of each chapter.This easy-to-follow work illuminates how concepts from fundamental and advanced mathematics can be applied to solve a broad range of image data mining problems encountered by students and researchers of computer science. Students of mathematics and other scientific disciplines will also benefit from the applications and solutions described in the text, together with the hands-on exercises that enable the reader to gain first-hand experience of computing.
Описание: Introduction.- Hyperspectral Imaging System.- Classification Techniques for HSI.- Preprocessing: Noise Reduction/ Band Categorization for HSI.- Spatial Feature Extraction Using Segmentation.- Multiple Deep learning models for feature extraction in classification.- Deep learning for merging spatial and spectral information in classification.- Sparse cording for Hyperspectral Data.- Classification Applications of HSI classification.- Conclusion.
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