Generating Images of Stratification is a self-contained presentation of a theoretical research program that deals with a significant explanatory problem relating to social inequality and that constructs generative theoretical models in doing so. In more detail: -Self-contained presentation - In respect to the background sociological facts and theoretical ideas and also the formal methods the book provides clear and simple accounts accompanied by examples. - A theoretical research program - The emphasis is on theory development, involving a series of theoretical models constructed within a core framework of principles and methods. - Deals with a significant explanatory problem relating to social inequality - We know from research that how people perceive the stratification system of a society depends upon their position in that system. So the problem is: What process generates this regularity and thereby explains empirical generalizations about the social structuration of images? - Constructs generative theoretical models - The book is an extended presentation of "generative theory" in sociology, a formal method of producing effective theoretical explanations. Generating Images of Stratification is of interest to mathematical sociologists and formal theorists in sociology; sociologists interested in social stratification; methodologists, both in sociology and in other fields; philosophers of social science; and theoretical scientists and mathematicians who are interested in applying their analytical tools to social science topics.

This three-volume set LNCS 11901, 11902, and 11903 constitutes the refereed conference proceedings of the 10thth International Conference on Image and Graphics, ICIG 2019, held in Beijing, China, in August 2019. The 183 full papers presented were selected from 384 submissions and focus on advances of theory, techniques and algorithms as well as innovative technologies of image, video and graphics processing and fostering innovation, entrepreneurship, and networking.

The two volume set LNCS 9256 and 9257 constitutes the refereed proceedings of the 16th International Conference on Computer Analysis of Images and Patterns, CAIP 2015, held in Valletta, Malta, in September 2015. The 138 papers presented were carefully reviewed and selected from numerous submissions. CAIP 2015 is the sixteenth in the CAIP series of biennial international conferences devoted to all aspects of computer vision, image analysis and processing, pattern recognition, and related fields.

This book constitutes the refereed proceedings of the 5th International Conference on Image Analysis and Recognition, ICIAR 2008, held in Póvoa do Varzim, Portugal, in June 2008. The 110 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 226 submissions. The papers are organized in topical sections on image restoration and enhancement, image and video segmentation, non-linear image processing, image and video coding and encryption, indexing and retrieval, computer vision, feature extraction and classification, shape representation and matching, object recognition, character recognition, texture and motion analysis, tracking, biomedical image analysis, biometrics, face recognition, and a special session on recent advances in multimodal biometric systems and applications.

Java is the preferred language for many of today’s leading-edge technologies—everything from smartphones and game consoles to robots, massive enterprise systems, and supercomputers. If you’re new to Java, the fourth edition of this bestselling guide provides an example-driven introduction to the latest language features and APIs in Java 6 and 7. Advanced Java developers will be able to take a deep dive into areas such as concurrency and JVM enhancements. You’ll learn powerful new ways to manage resources and exceptions in your applications, and quickly get up to speed on Java’s new concurrency utilities, and APIs for web services and XML. You’ll also find an updated tutorial on how to get started with the Eclipse IDE, and a brand-new introduction to database access in Java.

Leveraging the latest developments in MATLAB and its image processing toolbox, this 'cookbook' is a collection of 30 practical recipes for image processing, ranging from foundational techniques to recently published algorithms. Presented in a clear and meaningful sequence, these recipes are prepared with the reader in mind, allowing one to focus on particular topics or read as a whole from cover to cover. Key Features: A practical, user-friendly guide that equips researchers and practitioners with the tools to implement efficient image processing workflows in MATLAB. Each recipe is presented through clear, step-by-step instructions and rich visual examples. Each recipe contains its own source code, explanations, and figures, making the book an excellent standalone resource for quick reference. Strategically structured to aid sequential learning, yet with self-contained chapters for those seeking solutions to specific image processing challenges. The book serves as a concise and readable practical reference to deploy image processing pipelines in MATLAB quickly and efficiently. With its accessible and practical approach, the book is a valuable guide for those who navigate this evolving area, including researchers, students, developers, and practitioners in the fields of image processing, computer vision, and image analysis.

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019. The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: optical imaging; endoscopy; microscopy. Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression. Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging. Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis. Part V: computer assisted interventions; MIC meets CAI. Part VI: computed tomography; X-ray imaging.