Pattern Recognition and Information Forensics


Book Description

This book constitutes the refereed post-conference proceedings of 3 workshops, held at the 24th International Conference on Pattern Recognition, Beijing, China, in August 2018: the Third International Workshop on Computer Vision for Analysis of Underwater Imagery, CVAUI 2018, the 7th International Workshop on Computational Forensics, IWCF 2018, and the International Workshop on Multimedia Information Processing for Personality and Social Networks Analysis, MIPPSNA 2018.The 16 full papers presented in this book were carefully reviewed and selected from 23 submissions. CVAUI Workshop: The analysis of underwater imagery imposes a series of unique challenges, which need to be tackled by the computer vision community in collaboration with biologists and ocean scientists. IWCF Workshop: With the advent of high-end technology, fraudulent efforts are on rise in many areas of our daily life, may it be fake paper documents, forgery in the digital domain or copyright infringement. In solving the related criminal cases use of pattern recognition (PR) principles is also gaining an important place because of their ability in successfully assisting the forensic experts to solve many of such cases. MIPPSNA Workshop: Its goal is to compile the latest research advances on the analysis of multimodal information for facing problems that are not visually obvious, this is, problems for which the sole visual analysis is insufficient to provide a satisfactory solution.




Dark Web Pattern Recognition and Crime Analysis Using Machine Intelligence


Book Description

"The reference book will show the depth of Darkweb Environment by highlighting the Attackers techniques, crawling of hidden contents, Intrusion detection using advance algorithms, TOR Network structure, Memex search engine indexing of anonymous contents at Online Social Network, and more"--




Pattern Recognition and Classification in Time Series Data


Book Description

Patterns can be any number of items that occur repeatedly, whether in the behaviour of animals, humans, traffic, or even in the appearance of a design. As technologies continue to advance, recognizing, mimicking, and responding to all types of patterns becomes more precise. Pattern Recognition and Classification in Time Series Data focuses on intelligent methods and techniques for recognizing and storing dynamic patterns. Emphasizing topics related to artificial intelligence, pattern management, and algorithm development, in addition to practical examples and applications, this publication is an essential reference source for graduate students, researchers, and professionals in a variety of computer-related disciplines.




Personnel Selection in the Pattern Evidence Domain of Forensic Science


Book Description

In July 2016 The National Academies of Sciences, Engineering, and Medicine convened a workshop with the goal of bringing together industrial and organizational (I-O) psychologists, experts on personnel selection and testing, forensic scientists, and other researchers whose work has a nexus with workforce needs in the forensic science field with a focus on pattern evidence. Participants reviewed the current status of selection and training of forensic scientists who specialize in pattern evidence and discussed how tools used in I-O psychology to understand elements of a task and measure aptitude and performance could address challenges in the pattern evidence domain of the forensic sciences. This publication summarizes the presentations and discussions from the workshop.




Pattern Recognition


Book Description

Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to "learn" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10 years of teaching experience, the text was developed by the authors through use in their own classrooms.*Approaches pattern recognition from the designer's point of view*New edition highlights latest developments in this growing field, including independent components and support vector machines, not available elsewhere*Supplemented by computer examples selected from applications of interest




Pattern Recognition, Machine Intelligence and Biometrics


Book Description

"Pattern Recognition, Machine Intelligence and Biometrics" covers the most recent developments in Pattern Recognition and its applications, using artificial intelligence technologies within an increasingly critical field. It covers topics such as: image analysis and fingerprint recognition; facial expressions and emotions; handwriting and signatures; iris recognition; hand-palm gestures; and multimodal based research. The applications span many fields, from engineering, scientific studies and experiments, to biomedical and diagnostic applications, to personal identification and homeland security. In addition, computer modeling and simulations of human behaviors are addressed in this collection of 31 chapters by top-ranked professionals from all over the world in the field of PR/AI/Biometrics. The book is intended for researchers and graduate students in Computer and Information Science, and in Communication and Control Engineering. Dr. Patrick S. P. Wang is a Professor Emeritus at the College of Computer and Information Science, Northeastern University, USA, Zijiang Chair of ECNU, Shanghai, and NSC Visiting Chair Professor of NTUST, Taipei.




Pattern Recognition Applications in Engineering


Book Description

The implementation of data and information analysis has become a trending solution within multiple professions. New tools and approaches are continually being developed within data analysis to further solve the challenges that come with professional strategy. Pattern recognition is an innovative method that provides comparison techniques and defines new characteristics within the information acquisition process. Despite its recent trend, a considerable amount of research regarding pattern recognition and its various strategies is lacking. Pattern Recognition Applications in Engineering is an essential reference source that discusses various strategies of pattern recognition algorithms within industrial and research applications and provides examples of results in different professional areas including electronics, computation, and health monitoring. Featuring research on topics such as condition monitoring, data normalization, and bio-inspired developments, this book is ideally designed for analysts; researchers; civil, mechanical, and electronic engineers; computing scientists; chemists; academicians; and students.




Introduction to Pattern Recognition


Book Description

Introduction to Pattern Recognition: A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas' Pattern Recognition. It includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision. - Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition, Fourth Edition - Solved examples in Matlab, including real-life data sets in imaging and audio recognition - Available separately or at a special package price with the main text (ISBN for package: 978-0-12-374491-3)




Introduction to Statistical Pattern Recognition


Book Description

This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a wide range of problems: it is applied to engineering problems, such as character readers and wave form analysis as well as to brain modeling in biology and psychology. Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition. This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapter contains computer projects as well as exercises.




Advances in Pattern Recognition


Book Description

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