Clustering Methods for Big Data Analytics (Unsupervised and Semi-Supervised Learning)
This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health,...
Image Analysis and Recognition (Lecture Notes in Computer Science, #3212)
by Aurelio Campilho
Pattern Recognition and Machine Learning (Information Science and Statistics)
by Christopher M. Bishop
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebr...
Cancer Prevention Through Early Detection (Lecture Notes in Computer Science, #13581)
This book constitutes the refereed proceedings of the first International Workshop on Cancer Prevention through Early Detection, CaPTion, held in conjunction with the 25th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2022, in Singapore, Singapore, in September 2022. The 16 papers presented at CaPTion 2022 were carefully reviewed and selected from 21 submissions. The workshop invites researchers to submit their work in the field of medical imaging aroun...
This book presents the complex topic of using computational intelligence for pattern recognition in a straightforward and applicable way, using Matlab to illustrate topics and concepts. The author covers computational intelligence tools like particle swarm optimization, bacterial foraging, simulated annealing, genetic algorithm, and artificial neural networks. The Matlab based illustrations along with the code are given for every topic. Readers get a quick basic understanding of various pattern...
Visual Surveillance
The 11 contributions from the June 1999 workshop are grouped under the headings of people detection and tracking, probabilistic and statistical methods, and calibration and implementation. Among the topics are multi-camera color tracking, a Bayesian approach to human activity recognition, using mode
Invariant Methods in Discrete and Computational Geometry
Invariant, or coordinate-free methods provide a natural framework for many geometric questions. Invariant Methods in Discrete and Computational Geometry provides a basic introduction to several aspects of invariant theory, including the supersymmetric algebra, the Grassmann-Cayler algebra, and Chow forms. It also presents a number of current research papers on invariant theory and its applications to problems in geometry, such as automated theorem proving and computer vision. Audience:...
Intelligent Systems for Crisis Management (Lecture Notes in Geoinformation and Cartography)
In the past several years, there have been significant technological advances in the field of crisis response. However, many aspects concerning the efficient collection and integration of geo-information, applied semantics and situation awareness for disaster management remain open. Improving crisis response systems and making them intelligent requires extensive collaboration between emergency responders, disaster managers, system designers and researchers alike. To facilitate this process, the...
The Structure of Style
Style is a fundamental and ubiquitous aspect of the human experience: Everyone instantly and constantly assesses people and things according to their individual styles, academics establish careers by researching musical, artistic, or architectural styles, and entire industries maintain themselves by continuously creating and marketing new styles. Yet what exactly style is and how it works are elusive: We certainly know it when we see it, but there is no shared and clear understanding of the dive...
Based on the seminar that took place in Dagstuhl, Germany in June 2011, this contributed volume studies the four important topics within the scientific visualization field: uncertainty visualization, multifield visualization, biomedical visualization and scalable visualization. * Uncertainty visualization deals with uncertain data from simulations or sampled data, uncertainty due to the mathematical processes operating on the data, and uncertainty in the visual representation,* Multifield visual...
This volume constitutes selected papers presented during the Second International Conference on Intelligent Systems and Pattern Recognition, ISPR 2022, held in Hammamet, Tunisia, in March 2022. Due to the COVID-19 pandemic the conference was held online. The 22 full papers and 10 short papers presented were thoroughly reviewed and selected from the 91 submissions. The papers are organized in the following topical sections: computer vision; data mining; pattern recognition; machine and deep lear...
Statistical Models of Shape: Optimisation and Evaluation
by Rhodri Davies, Carole Twining, and Professor Chris Taylor
Advanced ActionScript 3.0 Animation (Friends of Ed Adobe Learning Library)
by Keith Peters
This book is a compilation of advanced ActionScript 3.0 animation techniques for any user creating games, user interaction, or motion control with ActionScript. It's an anthology of topics that follow from the author's earlier book, Foundation ActionScript 3.0 Animation: Making Things Move, and things that became possible in version 10 of Flash Player. This book covers a diverse selection of topics that don't necessarily lead one into the other. You don't need to start with Chapter 1 and read it...
This book constitutes the refereed proceedings of the Second International Workshop on Machine Learning in Medical Imaging, MLMI 2011, held in conjunction with MICCAI 2011, in Toronto, Canada, in September 2011. The 44 revised full papers presented were carefully reviewed and selected from 74 submissions. The papers focus on major trends in machine learning in medical imaging aiming to identify new cutting-edge techniques and their use in medical imaging.
Iris Biometrics: From Segmentation to Template Security (Advances in Information Security)
by Christian Rathgeb and Peter Wild
IEEE Workshop on Visual Languages, 1991, Proceedings, October 8-11, 1991, Kob Japan/91th0402-8
This book brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluating, interpreting and understanding biometric data. It naturally leads to topics including data mining and prediction to be examined in detail. The book places an emphasis on the various performance measures available for biometric systems, what they mean, and when they should and should not be applied. The evaluation techniques are presented rigorously, however they are always accompa...
An attempt is made in this book to give scientists a detailed working knowledge of the powerful mathematical tools available to aid in data interpretation, especially when con- fronted with large data sets incorporating many parameters. A minimal amount of com- puter knowledge is necessary for successful applications, and we have tried conscien- tiously to provide this in the appropriate sections and references. Scientific data are now being produced at rates not believed possible ten years ago....
Machine Learning Techniques for Gait Biometric Recognition
by James Eric Mason, Issa Traore, and Isaac Woungang
This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extr...
Machine Learning Systems for Multimodal Affect Recognition
by Markus Kachele
Markus Kächele offers a detailed view on the different steps in the affective computing pipeline, ranging from corpus design and recording over annotation and feature extraction to post-processing, classification of individual modalities and fusion in the context of ensemble classifiers. He focuses on multimodal recognition of discrete and continuous emotional and medical states. As such, specifically the peculiarities that arise during annotation and processing of continuous signals are highlig...
Speaker Authentication (Signals and Communication Technology)
by Qi (Peter) Li
This book focuses on use of voice as a biometric measure for personal authentication. In particular, "Speaker Recognition" covers two approaches in speaker authentication: speaker verification (SV) and verbal information verification (VIV). The SV approach attempts to verify a speaker's identity based on his/her voice characteristics while the VIV approach validates a speaker's identity through verification of the content of his/her utterance(s). SV and VIV can be combined for new applications....