Download or read book Statistical Machine Learning for Human Behaviour Analysis written by Thomas Moeslund and published by MDPI. This book was released on 2020-06-17 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Special Issue focused on novel vision-based approaches, mainly related to computer vision and machine learning, for the automatic analysis of human behaviour. We solicited submissions on the following topics: information theory-based pattern classification, biometric recognition, multimodal human analysis, low resolution human activity analysis, face analysis, abnormal behaviour analysis, unsupervised human analysis scenarios, 3D/4D human pose and shape estimation, human analysis in virtual/augmented reality, affective computing, social signal processing, personality computing, activity recognition, human tracking in the wild, and application of information-theoretic concepts for human behaviour analysis. In the end, 15 papers were accepted for this special issue. These papers, that are reviewed in this editorial, analyse human behaviour from the aforementioned perspectives, defining in most of the cases the state of the art in their corresponding field.

Download or read book Statistical Machine Learning for Human Behaviour Analysis written by Thomas Moeslund and published by . This book was released on 2020 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Special Issue focused on novel vision-based approaches, mainly related to computer vision and machine learning, for the automatic analysis of human behaviour. We solicited submissions on the following topics: information theory-based pattern classification, biometric recognition, multimodal human analysis, low resolution human activity analysis, face analysis, abnormal behaviour analysis, unsupervised human analysis scenarios, 3D/4D human pose and shape estimation, human analysis in virtual/augmented reality, affective computing, social signal processing, personality computing, activity recognition, human tracking in the wild, and application of information-theoretic concepts for human behaviour analysis. In the end, 15 papers were accepted for this special issue. These papers, that are reviewed in this editorial, analyse human behaviour from the aforementioned perspectives, defining in most of the cases the state of the art in their corresponding field.

Download or read book Behavior Analysis with Machine Learning Using R written by Enrique Garcia Ceja and published by CRC Press. This book was released on 2021-11-26 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Behavior Analysis with Machine Learning Using R introduces machine learning and deep learning concepts and algorithms applied to a diverse set of behavior analysis problems. It focuses on the practical aspects of solving such problems based on data collected from sensors or stored in electronic records. The included examples demonstrate how to perform common data analysis tasks such as: data exploration, visualization, preprocessing, data representation, model training and evaluation. All of this, using the R programming language and real-life behavioral data. Even though the examples focus on behavior analysis tasks, the covered underlying concepts and methods can be applied in any other domain. No prior knowledge in machine learning is assumed. Basic experience with R and basic knowledge in statistics and high school level mathematics are beneficial. Features: Build supervised machine learning models to predict indoor locations based on WiFi signals, recognize physical activities from smartphone sensors and 3D skeleton data, detect hand gestures from accelerometer signals, and so on. Program your own ensemble learning methods and use Multi-View Stacking to fuse signals from heterogeneous data sources. Use unsupervised learning algorithms to discover criminal behavioral patterns. Build deep learning neural networks with TensorFlow and Keras to classify muscle activity from electromyography signals and Convolutional Neural Networks to detect smiles in images. Evaluate the performance of your models in traditional and multi-user settings. Build anomaly detection models such as Isolation Forests and autoencoders to detect abnormal fish behaviors. This book is intended for undergraduate/graduate students and researchers from ubiquitous computing, behavioral ecology, psychology, e-health, and other disciplines who want to learn the basics of machine learning and deep learning and for the more experienced individuals who want to apply machine learning to analyze behavioral data.

Download or read book Human Behaviour Analysis Using Intelligent Systems written by D. Jude Hemanth and published by Springer Nature. This book was released on 2019-11-20 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human–computer interaction (HCI) is one of the most significant areas of computational intelligence. This book focuses on the human emotion analysis aspects of HCI, highlighting innovative methodologies for emotion analysis by machines/computers and their application areas. The methodologies are presented with numerical results to enable researchers to replicate the work. This multidisciplinary book is useful to researchers and academicians, as well as students wanting to pursue a career in computational intelligence. It can also be used as a handbook, reference book, and a textbook for short courses.

Download or read book Human Behavior Learning and Transfer written by Yangsheng Xu and published by CRC Press. This book was released on 2005-09-06 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bridging the gap between human-computer engineering and control engineering, Human Behavior Learning and Transfer delineates how to abstract human action and reaction skills into computational models. The authors include methods for modeling a variety of human action and reaction behaviors and explore processes for evaluating, optimizing, and transferring human skills. They also cover modeling continuous and discontinuous human control strategy and discuss simulation studies and practical real-life situations. The book examines how to model two main aspects of human behavior: reaction skills and action skills. It begins with a discussion of the various topics involved in human reaction skills modeling. The authors apply machine learning techniques and statistical analysis to abstracting models of human reaction control strategy. They contend that such models can be learned sufficiently to emulate complex human control behaviors in the feedback loop. The second half of the book explores issues related to human action skills modeling. The methods presented are based on techniques for reducing the dimensionality of data sets, while preserving as much useful information as possible. The modeling approaches developed are applied in real-life applications including navigation of smart wheel chairs and intelligent surveillance. Written in a consistent, easily approachable style, the book includes in-depth discussions of a broad range of topics. It provides the tools required to formalize human behaviors into algorithmic, machine-coded strategies.

Download or read book Behavioral Data Analysis with R and Python written by Florent Buisson and published by "O'Reilly Media, Inc.". This book was released on 2021-06-15 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the full power of the behavioral data in your company by learning tools specifically designed for behavioral data analysis. Common data science algorithms and predictive analytics tools treat customer behavioral data, such as clicks on a website or purchases in a supermarket, the same as any other data. Instead, this practical guide introduces powerful methods specifically tailored for behavioral data analysis. Advanced experimental design helps you get the most out of your A/B tests, while causal diagrams allow you to tease out the causes of behaviors even when you can't run experiments. Written in an accessible style for data scientists, business analysts, and behavioral scientists, thispractical book provides complete examples and exercises in R and Python to help you gain more insight from your data--immediately. Understand the specifics of behavioral data Explore the differences between measurement and prediction Learn how to clean and prepare behavioral data Design and analyze experiments to drive optimal business decisions Use behavioral data to understand and measure cause and effect Segment customers in a transparent and insightful way

Download or read book Machine Learning for Social and Behavioral Research written by Ross Jacobucci and published by Guilford Publications. This book was released on 2023-07-31 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Over the past 20 years, there has been an incredible change in the size, structure, and types of data collected in the social and behavioral sciences. Thus, social and behavioral researchers have increasingly been asking the question: "What do I do with all of this data?" The goal of this book is to help answer that question. It is our viewpoint that in social and behavioral research, to answer the question "What do I do with all of this data?", one needs to know the latest advances in the algorithms and think deeply about the interplay of statistical algorithms, data, and theory. An important distinction between this book and most other books in the area of machine learning is our focus on theory"--

Download or read book Brain inspired Machine Learning and Computation for Brain Behavior Analysis written by Rong Chen and published by Frontiers Media SA. This book was released on 2021-04-16 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Download or read book Data Analysis with Machine Learning for Psychologists written by Chandril Ghosh and published by Springer Nature. This book was released on 2022-10-17 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: The power of data drives the digital economy of the 21st century. It has been argued that data is as vital a resource as oil was during the industrial revolution. An upward trend in the number of research publications using machine learning in some of the top journals in combination with an increasing number of academic recruiters within psychology asking for Python knowledge from applicants indicates a growing demand for these skills in the market. While there are plenty of books covering data science, rarely, if ever, books in the market address the need of social science students with no computer science background. They are typically written by engineers or computer scientists for people of their discipline. As a result, often such books are filled with technical jargon and examples irrelevant to psychological studies or projects. In contrast, this book was written by a psychologist in a simple, easy-to-understand way that is brief and accessible. The aim for this book was to make the learning experience on this topic as smooth as possible for psychology students/researchers with no background in programming or data science. Completing this book will also open up an enormous amount of possibilities for quantitative researchers in psychological science, as it will enable them to explore newer types of research questions.

Download or read book Understanding Machine Learning written by Shai Shalev-Shwartz and published by Cambridge University Press. This book was released on 2014-05-19 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.

Download or read book Visual Analysis of Behaviour written by Shaogang Gong and published by Springer Science & Business Media. This book was released on 2011-05-26 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive treatment of visual analysis of behaviour from computational-modelling and algorithm-design perspectives. Topics: covers learning-group activity models, unsupervised behaviour profiling, hierarchical behaviour discovery, learning behavioural context, modelling rare behaviours, and “man-in-the-loop” active learning; examines multi-camera behaviour correlation, person re-identification, and “connecting-the-dots” for abnormal behaviour detection; discusses Bayesian information criterion, Bayesian networks, “bag-of-words” representation, canonical correlation analysis, dynamic Bayesian networks, Gaussian mixtures, and Gibbs sampling; investigates hidden conditional random fields, hidden Markov models, human silhouette shapes, latent Dirichlet allocation, local binary patterns, locality preserving projection, and Markov processes; explores probabilistic graphical models, probabilistic topic models, space-time interest points, spectral clustering, and support vector machines.

Download or read book Facets of Behaviormetrics written by Akinori Okada and published by Springer Nature. This book was released on 2023-09-17 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book is the first one written in English that deals comprehensively with behavior metrics. The term “behaviormetrics” comprehends the research including all sorts of quantitative approaches to disclose human behavior. Researchers in behavior metrics have developed, extended, and improved methods such as multivariate statistical analysis, survey methods, cluster analysis, machine learning, multidimensional scaling, corresponding analysis or quantification theory, network analysis, clustering, factor analysis, test theory, and related factors. In the spirit of behavior metrics, researchers applied these methods to data obtained by surveys, experiments, or websites from a diverse range of fields. The purpose of this book is twofold. One is to represent studies that display how the basic elements of behavior metrics have developed into present-day behavior metrics. The other is to represent studies performed mainly by those who would like to pioneer new fields of behavior metrics and studies that display elements of future behavior metrics. These studies consist of various characteristics such as those dealing with theoretical or conceptual subjects, the algorithm, the model, the method, and the application to a wide variety of fields. This book helps readers to understand the present and future of behavior metrics.

Download or read book Methods of Behavior Analysis in Neuroscience written by Jerry J. Buccafusco and published by CRC Press. This book was released on 2000-08-29 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using the most well-studied behavioral analyses of animal subjects to promote a better understanding of the effects of disease and the effects of new therapeutic treatments on human cognition, Methods of Behavior Analysis in Neuroscience provides a reference manual for molecular and cellular research scientists in both academia and the pharmaceutic

Download or read book Computer Analysis of Human Behavior written by Albert Ali Salah and published by Springer Science & Business Media. This book was released on 2011-10-07 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a broad survey of advanced pattern recognition techniques for human behavior analysis. Clearly structured, the book begins with concise coverage of the major concepts, before introducing the most frequently used techniques and algorithms in detail, and then discussing examples of real applications. Features: contains contributions from an international selection of experts in the field; presents a thorough introduction to the fundamental topics of human behavior analysis; investigates methods for activity recognition, including gait and posture analysis, hand gesture analysis, and semantics of human behavior in image sequences; provides an accessible psychological treatise on social signals for the analysis of social behaviors; discusses voice and speech analysis, combined audiovisual cues, and social interactions and group dynamics; examines applications in different research fields; each chapter concludes with review questions, a summary of the topics covered, and a glossary.

Download or read book A Decadal Survey of the Social and Behavioral Sciences written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2019-06-26 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: The primary function of the intelligence analyst is to make sense of information about the world, but the way analysts do that work will look profoundly different a decade from now. Technological changes will bring both new advances in conducting analysis and new risks related to technologically based activities and communications around the world. Because these changes are virtually inevitable, the Intelligence Community will need to make sustained collaboration with researchers in the social and behavioral sciences (SBS) a key priority if it is to adapt to these changes in the most productive ways. A Decadal Survey Of The Social and Behavioral Sciences provides guidance for a 10-year research agenda. This report identifies key opportunities in SBS research for strengthening intelligence analysis and offers ideas for integrating the knowledge and perspectives of researchers from these fields into the planning and design of efforts to support intelligence analysis.

Download or read book Machine Learning Methods for Behaviour Analysis and Anomaly Detection in Video written by Olga Isupova and published by Springer. This book was released on 2018-02-24 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis proposes machine learning methods for understanding scenes via behaviour analysis and online anomaly detection in video. The book introduces novel Bayesian topic models for detection of events that are different from typical activities and a novel framework for change point detection for identifying sudden behavioural changes. Behaviour analysis and anomaly detection are key components of intelligent vision systems. Anomaly detection can be considered from two perspectives: abnormal events can be defined as those that violate typical activities or as a sudden change in behaviour. Topic modelling and change-point detection methodologies, respectively, are employed to achieve these objectives. The thesis starts with the development of learning algorithms for a dynamic topic model, which extract topics that represent typical activities of a scene. These typical activities are used in a normality measure in anomaly detection decision-making. The book also proposes a novel anomaly localisation procedure. In the first topic model presented, a number of topics should be specified in advance. A novel dynamic nonparametric hierarchical Dirichlet process topic model is then developed where the number of topics is determined from data. Batch and online inference algorithms are developed. The latter part of the thesis considers behaviour analysis and anomaly detection within the change-point detection methodology. A novel general framework for change-point detection is introduced. Gaussian process time series data is considered. Statistical hypothesis tests are proposed for both offline and online data processing and multiple change point detection are proposed and theoretical properties of the tests are derived. The thesis is accompanied by open-source toolboxes that can be used by researchers and engineers.