Probabilistic Graphical Model for Computer Vision

Graphical models are a statistical tool used for a wide range of applications. There has been a huge amount of research in this topic across statistics, mathematics and computer science in the last fe

This friendly guide is the companion you need to convert pure mathematics into understanding and facility with a host of probabilistic tools. The book provides a high-level view of probability and its most powerful applications. It begins with the basic rules of probability and quickly progresses to some of the most sophisticated modern techniques in use, including Kalman filters, Monte Carlo techniques, machine learning methods, Bayesian inference and stochastic processes. It draws on thirty years of experience in applying probabilistic methods to problems in computational science and engineering, and numerous practical examples illustrate where these techniques are used in the real world. Topics of discussion range from carbon dating to Wasserstein GANs, one of the most recent developments in Deep Learning. The underlying mathematics is presented in full, but clarity takes priority over complete rigour, making this text a starting reference source for researchers and a readable overv

This friendly guide is the companion you need to convert pure mathematics into understanding and facility with a host of probabilistic tools. The book provides a high-level view of probability and its most powerful applications. It begins with the basic rules of probability and quickly progresses to some of the most sophisticated modern techniques in use, including Kalman filters, Monte Carlo techniques, machine learning methods, Bayesian inference and stochastic processes. It draws on thirty years of experience in applying probabilistic methods to problems in computational science and engineering, and numerous practical examples illustrate where these techniques are used in the real world. Topics of discussion range from carbon dating to Wasserstein GANs, one of the most recent developments in Deep Learning. The underlying mathematics is presented in full, but clarity takes priority over complete rigour, making this text a starting reference source for researchers and a readable overv

3D Printing for Model Engineersis the first truly comprehensive guide to 3D printing in the context of other creating engineering-based hobbies. It covers using 3D Computer Aided Design; 3D print

Visual pattern analysis is a fundamental tool in mining data for knowledge. Computational representations for patterns and texture allow us to summarize, store, compare, and label in order to learn ab

Computer Vision for Assistive Healthcare describes how advanced computer vision techniques provide tools to support common human needs, such as mental functioning, personal mobility, sensory functions

Model checking is a computer-assisted method for the analysis of dynamical systems that can be modeled by state-transition systems. Drawing from research traditions in mathematical logic, programming

Funny and totally true childhood biographies and full-color illustrations tell tales from the challenging yet defining growing-up years of Albert Einstein, Jane Goodall, Marie Curie, and 12 other brilliant scientists.Every great scientist started out as a kid. Before their experiments, inventions, and discoveries that changed the world, the world's most celebrated scientists had regular-kid problems just like you.*Stephen Hawking hated school, and preferred to spend his free time building model airplanes, inventing board games, and even building his own computer.*Jane Goodall got in trouble for bringing worms and snails into her house.*And Neil deGrasse Tyson had to start a dog-walking business to save up money to buy a telescope.Readers ages 8 to 12 years old will learn all the stories of a diverse and inclusive group—also including Temple Grandin, Nikola Tesla, Ada Lovelace, Benjamin Franklin, Isaac Newton, Rosalind Franklin, Sally Ride, Rachel Carson, George Washington Carver, and V

In Synthetic Vision: Using Volume Learning and Visual DNA, a holistic model of the human visual system is developed into a working model in C++, informed by the latest neuroscience, DNN, and computer

This volume provides a practical introduction to the method of maximum likelihood as used in social science research. Ward and Ahlquist focus on applied computation in R and use real social science data from actual, published research. Unique among books at this level, it develops simulation-based tools for model evaluation and selection alongside statistical inference. The book covers standard models for categorical data as well as counts, duration data, and strategies for dealing with data missingness. By working through examples, math, and code, the authors build an understanding about the contexts in which maximum likelihood methods are useful and develop skills in translating mathematical statements into executable computer code. Readers will not only be taught to use likelihood-based tools and generate meaningful interpretations, but they will also acquire a solid foundation for continued study of more advanced statistical techniques.

Our world and the people within it are increasingly interpreted and classified by automated systems. At the same time, automated classifications influence what happens in the physical world. These entanglements change what it means to interact with governance, and shift what elements of our identity are knowable and meaningful. In this cyber-physical world, or 'world state', what is the role for law? Specifically, how should law address the claim that computational systems know us better than we know ourselves? Monitoring Laws traces the history of government profiling from the invention of photography through to emerging applications of computer vision for personality and behavioral analysis. It asks what dimensions of profiling have provoked legal intervention in the past, and what is different about contemporary profiling that requires updating our legal tools. This work should be read by anyone interested in how computation is changing society and governance, and what it is about p

In this comprehensive textbook about robot grasping, readers will discover an integrated look at the major concepts and technical results in robot grasp mechanics. A large body of prior research, including key theories, graphical techniques, and insights on robot hand designs, is organized into a systematic review, using common notation and a common analytical framework. With introductory and advanced chapters that support senior undergraduate and graduate level robotics courses, this book provides a full introduction to robot grasping principles that are needed to model and analyze multi-finger robot grasps, and serves as a valuable reference for robotics students, researchers, and practicing robot engineers. Each chapter contains many worked-out examples, exercises with full solutions, and figures that highlight new concepts and help the reader master the use of the theories and equations presented.

Network flow theory has been used across a number of disciplines, including theoretical computer science, operations research, and discrete math, to model not only problems in the transportation of goods and information, but also a wide range of applications from image segmentation problems in computer vision to deciding when a baseball team has been eliminated from contention. This graduate text and reference presents a succinct, unified view of a wide variety of efficient combinatorial algorithms for network flow problems, including many results not found in other books. It covers maximum flows, minimum-cost flows, generalized flows, multicommodity flows, and global minimum cuts and also presents recent work on computing electrical flows along with recent applications of these flows to classical problems in network flow theory.

Is the human mind uniquely nonphysical or even spiritual, such that divine intentions can meet physical realities? As scholars in science and religion have spent decades attempting to identify a 'causal joint' between God and the natural world, human consciousness has been often privileged as just such a locus of divine-human interaction. However, this intuitively dualistic move is both out of step with contemporary science and theologically insufficient. By discarding the God-nature model implied by contemporary noninterventionist divine action theories, one is freed up to explore theological and metaphysical alternatives for understanding divine action in the mind. Sarah Lane Ritchie suggests that a theologically robust theistic naturalism offers a more compelling vision of divine action in the mind. By affirming that to be fully natural is to be involved with God's active presence, one may affirm divine action not only in the human mind, but throughout the natural world.

Python is today's fastest growing programming language. This engaging and refreshingly different guide breaks down the skills into clear step-by-step chunks and explains the theory using brief easy-to-understand language. Rather than bamboozling readers with pages of mind-numbing technical jargon, this book includes 150 practical challenges, putting the power in the reader's hands. Through creating programs to solve these challenges the reader will quickly progress from mastering the basics to confidently using subroutines, a graphical user interface, and linking to external text, csv and SQL files. This book is perfect for anyone who wants to learn how to program with Python. In particular, students starting out in computer science and teachers who want to improve their confidence in Python will find here a set of ready-made challenges for classroom use.

Quantum theory is the soul of theoretical physics. It is not just a theory of specific physical systems, but rather a new framework with universal applicability. This book shows how we can reconstruct the theory from six information-theoretical principles, by rebuilding the quantum rules from the bottom up. Step by step, the reader will learn how to master the counterintuitive aspects of the quantum world, and how to efficiently reconstruct quantum information protocols from first principles. Using intuitive graphical notation to represent equations, and with shorter and more efficient derivations, the theory can be understood and assimilated with exceptional ease. Offering a radically new perspective on the field, the book contains an efficient course of quantum theory and quantum information for undergraduates. It is aimed at researchers, professionals, and students in physics, computer science and philosophy, as well as the curious outsider seeking a deeper understanding of the theo

In this volume, Mark Douglas offers a new vision of the history of Christian pacifism within the context of a warming world. He narrates this story in a way that recognizes the complexities of the tradition and aligns it with a coherent theological vision, one that shapes the tradition to encompass the new causes and types of wars fought during the Anthropocene. Along the way, Douglas draws from research in historical climatology to recover the overlooked role that climate changes have always played in shaping not only the Christian pacifist tradition but also the movement of traditions through western history. Scholars across a range of disciplines - peace studies, Christian theology and history, environmentalism, and environmental conflict studies - will benefit from this model of critical and charitable engagement with the complex history of Christian pacifism, the resources of which will be important for addressing wars in a warming world.

Recent years have witnessed an explosion in the volume and variety of data collected in all scientific disciplines and industrial settings. Such massive data sets present a number of challenges to researchers in statistics and machine learning. This book provides a self-contained introduction to the area of high-dimensional statistics, aimed at the first-year graduate level. It includes chapters that are focused on core methodology and theory - including tail bounds, concentration inequalities, uniform laws and empirical process, and random matrices - as well as chapters devoted to in-depth exploration of particular model classes - including sparse linear models, matrix models with rank constraints, graphical models, and various types of non-parametric models. With hundreds of worked examples and exercises, this text is intended both for courses and for self-study by graduate students and researchers in statistics, machine learning, and related fields who must understand, apply, and ad

If you’re a developer familiar with AI, machine learning, and computer vision, this practical book provides you with a foundational understanding of augmented and virtual reality functions. AR a

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using r

What is the future of curatorship? Is there a vision for an ideal model, a curatopia, whether in the form of a utopia or dystopia? Or is there a plurality of approaches, amounting to a curatorial hete

An account of modernization and technological innovation in nineteenth-century Brazil that provides a distinctly Brazilian perspective. Existing scholarship on the period describes the beginnings of Brazilian modernization as a European or North American import dependent on foreign capital, transfers of technology, and philosophical inspiration. Promoters of modernization were considered few in number, derivative in their thinking, or thwarted by an entrenched slaveholding elite hostile to industrialization. Teresa Cribelli presents a more nuanced picture. Nineteenth-century Brazilians selected among the transnational flow of ideas and technologies with care and attention to the specific conditions of their tropical nation. Studying underutilized sources, Cribelli illuminates a distinctly Brazilian vision of modernization that challenges the view that Brazil, a nation dependent on slave labor for much of the nineteenth century, was merely reactive in the face of the modernization model

This volume provides a practical introduction to the method of maximum likelihood as used in social science research. Ward and Ahlquist focus on applied computation in R and use real social science data from actual, published research. Unique among books at this level, it develops simulation-based tools for model evaluation and selection alongside statistical inference. The book covers standard models for categorical data as well as counts, duration data, and strategies for dealing with data missingness. By working through examples, math, and code, the authors build an understanding about the contexts in which maximum likelihood methods are useful and develop skills in translating mathematical statements into executable computer code. Readers will not only be taught to use likelihood-based tools and generate meaningful interpretations, but they will also acquire a solid foundation for continued study of more advanced statistical techniques.

In Borges' Classics, Laura Jansen reads the oeuvre of the Argentine author Jorge Luis Borges as a radically globalized model for reimagining our relationship with the classical past. This major study reveals how Borges constructs a new 'physics of reading' the classics, which privileges a paradoxical vision of the canon as universal yet centreless, and eschews fixed ideas about the cultural history of the West. Borges' unique approach transforms classical antiquity into a simultaneously familiar and remote world, whose legacy is both urgent and unstable. In the process, Borges repositions the classical tradition at the intersection of the traditional Western canon and modernist literature of the peripheral West. Jansen's study traces Borges' encounters with the classics through appeal to themes central to Borges' thought, such as history and fiction, memory and forgetfulness, the data of the senses, and the vectors that connect cultures and countries.

The computer has increasingly become the principal model for the mind, which means our most basic experience of "reality" is as mediated through a screen, or stored in a cloud. As a result, we are los

In Calvin's Political Theology and the Public Engagement of the Church, Matthew J. Tuininga explores a little appreciated dimension of John Calvin's political thought, his two kingdoms theology, as a model for constructive Christian participation in liberal society. Widely misunderstood as a proto-political culture warrior, due in part to his often misinterpreted role in controversies over predestination and the heretic Servetus, Calvin articulated a thoughtful approach to public life rooted in his understanding of the gospel and its teaching concerning the kingdom of God. He staked his ministry in Geneva on his commitment to keeping the church distinct from the state, abandoning simplistic approaches that placed one above the other, while rejecting the temptations of sectarianism or separatism. This revealing analysis of Calvin's vision offers timely guidance for Christians seeking a mode of faithful, respectful public engagement in democratic, pluralistic communities today.

Investment arbitration has emerged from modest beginnings and matured into an established presence in international law. However, in recent years it has drifted from the reciprocal vision of its founders. This volume serves as a comprehensive guide for those who wish to reform international investment law from within, seeking a return to the mutuality of access that is in arbitration's essence. A detailed toolset is provided for enhancing the access of host States and their nationals to formal resolution mechanisms in foreign investment disputes. It concludes by offering model texts to achieve greater reciprocity and access to justice in the settlement of disputes arising from international investment initiatives. The book will appeal to all those interested in the future of international investment law, including an international audience of scholars, government officials, private sector actors, and private citizens alike, and including diverse constituencies, communities, and collect

Written by some major contributors to the development of this class of graphical models, Chain Event Graphs introduces a viable and straightforward new tool for statistical inference, model se

Deploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Pytho

Network flow theory has been used across a number of disciplines, including theoretical computer science, operations research, and discrete math, to model not only problems in the transportation of goods and information, but also a wide range of applications from image segmentation problems in computer vision to deciding when a baseball team has been eliminated from contention. This graduate text and reference presents a succinct, unified view of a wide variety of efficient combinatorial algorithms for network flow problems, including many results not found in other books. It covers maximum flows, minimum-cost flows, generalized flows, multicommodity flows, and global minimum cuts and also presents recent work on computing electrical flows along with recent applications of these flows to classical problems in network flow theory.

The computer has increasingly become the principal model for the mind, which means our most basic experience of "reality" is as mediated through a screen, or stored in a cloud. As a result, we are los