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Data Complexity in Pattern Recognition
Automatic pattern recognition has uses in science and engineering, social sciences and finance. This book examines data complexity and its role in shaping theory and techniques across many disciplines, probing strengths and deficiencies of current classification techniques, and the algorithms that drive them. The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations for classification performance.
Structural, Syntactic, and Statistical Pattern Recognition
This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2018, held in Beijing, China, in August 2018. The 49 papers presented in this volume were carefully reviewed and selected from 75 submissions. They were organized in topical sections named: classification and clustering; deep learning and neurla networks; dissimilarity representations and Gaussian processes; semi and fully supervised learning methods; spatio-temporal pattern recognition and shape analysis; structural matching; multimedia analysis and understanding; and graph-theoretic methods.
Exploring Hong Kong
Exploring Hong Kong presents a vivid and multidimensional portrait of Hong Kong, one of Asia's most exciting cities. Inspired by his 20-year love affair with Hong Kong, Steven K. Bailey has transformed the typical Hong Kong guidebook by dispensing with the usual laundry lists of sights, hotels, and restaurants. In their place are thoughtfully written chapters that offer the author's personal perspective on how to best explore Hong Kong. From dolphin watches and back-country hikes to street markets, temples, and ferry rides, Exploring Hong Kong contains 40 richly detailed experiences that will unite travelers with the soul of one of the most dynamic cities in Asia. Book jacket.
Introduction And Fundamental Concepts Of Machine Learning
The field of machine learning is gaining a lot of attention around the world, both in the research community and in the business world. Learning by machine is becoming increasingly important in many aspects of modern life. Deep learning neural networks have been responsible for several recent technological advances, including those in the fields of computer vision, voice processing, machine translation, and reinforcement learning. As a direct consequence of this, neural networks have developed into an indispensable instrument in the toolset of every data scientist. This book explains neural networks, including what they are, why they are effective algorithms and why they have the structure t...
Ensemble Methods in Data Mining
Ensemble methods have been called the most influential development in Data Mining and Machine Learning in the past decade. They combine multiple models into one usually more accurate than the best of its components. Ensembles can provide a critical boost to industrial challenges -- from investment timing to drug discovery, and fraud detection to recommendation systems -- where predictive accuracy is more vital than model interpretability. Ensembles are useful with all modeling algorithms, but this book focuses on decision trees to explain them most clearly. After describing trees and their strengths and weaknesses, the authors provide an overview of regularization -- today understood to be a...
Structural, Syntactic, and Statistical Pattern Recognition
This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2018, held in Beijing, China, in August 2018. The 49 papers presented in this volume were carefully reviewed and selected from 75 submissions. They were organized in topical sections named: classification and clustering; deep learning and neurla networks; dissimilarity representations and Gaussian processes; semi and fully supervised learning methods; spatio-temporal pattern recognition and shape analysis; structural matching; multimedia analysis and understanding; and graph-theoretic methods.
Computational Intelligence and Bioinspired Systems
We present in this volume the collection of finally accepted papers of the eighth edition of the “IWANN” conference (“International Work-Conference on Artificial Neural Networks”). This biennial meeting focuses on the foundations, theory, models and applications of systems inspired by nature (neural networks, fuzzy logic and evolutionary systems). Since the first edition of IWANN in Granada (LNCS 540, 1991), the Artificial Neural Network (ANN) community, and the domain itself, have matured and evolved. Under the ANN banner we find a very heterogeneous scenario with a main interest and objective: to better understand nature and beings for the correct elaboration of theories, models an...
Image Analysis and Processing – ICIAP 2005
This volume contains the Proceedings of the 13th International Conference on Image Analysis and Processing (ICIAP 2005), held in Cagliari, Italy, at the conference centre “Centro della Cultura e dei Congressi”, on September 6–8, 2005. ICIAP 2005 was the thirteenth edition of a series of conferences organized every two years by the Italian group of researchersa?liated to the International Association for Pattern Recognition (GIRPR) with the aim to bring together researchers in image processing and pattern recognition from around the world. As for the previous editions, conference topics concerned the theory of image analysis and processing and its classical and Internet-driven applicati...
Management Innovation and Big Data
Adhering to the combination of theoretical introduction and practical case introduction, this book summarizes the basic concepts and methods in management and big data analysis at home and abroad and introduces a large number of relevant practical cases, especially new cases in the Internet era, to help readers integrate theoretical knowledge into practical applications. The chapters of this book are interrelated and independent of each other, making it easy for the reader to study in pieces or to delve deeper into a particular topic of interest. Covering an array of theories about management and big data at home and abroad, this book lays a solid foundation for being an authentic manager. I...
Document Analysis Systems VII
This book constitutes the refereed proceedings of the 7th International Conference on Document Analysis Systems, DAS 2006, held in Nelson, New Zealand, in February 2006. The 33 revised full papers and 22 poster papers presented were carefully reviewed and selected from 78 submissions. The papers are organized in topical sections on digital libraries, image processing, handwriting, document structure and format, tables, language and script identification, systems and performance evaluation, and retrieval and segmentation.
