Pattern recognition

It's hard to believe that it's been over a decade since One Jump Ahead: Challenging Human Supremacy at Checkers was published.

Privacy, Security and Trust within the Context of Pervasive Computing is an edited volume based on a post workshop at the second international conference on Pervasive Computing.

This textbook presents the main principles of visual analytics and describes techniques and approaches that have proven their utility and can be readily reproduced.

Introduction to Pattern Recognition: A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas' Pattern Recognition.

This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms.

This volume presents the results of the Neural Information Processing Systems Competition track  at the 2018 NeurIPS conference.

Advances in computer power and observing systems has led to the generation and accumulation of large scale weather & climate data begging for exploration and analysis.

The Practical, Step-by-Step Guide to Using LLMs at Scale in Projects and Products Large Language Models (LLMs) like ChatGPT are demonstrating breathtaking capabilities, but their size and complexity have deterred many practitioners from applying them.

Every mathematical discipline goes through three periods of development: the naive, the formal, and the critical.

Simplify next-generation deep learning by implementing powerful generative models using Python, TensorFlow and KerasKey FeaturesUnderstand the common architecture of different types of GANsTrain, optimize, and deploy GAN applications using TensorFlow and KerasBuild generative models with real-world data sets, including 2D and 3D dataBook DescriptionDeveloping Generative Adversarial Networks (GANs) is a complex task, and it is often hard to find code that is easy to understand.

Visual Computing for Medicine, Second Edition, offers cutting-edge visualization techniques and their applications in medical diagnosis, education, and treatment.

This must-read textbook presents an essential introduction to Kolmogorov complexity (KC), a central theory and powerful tool in information science that deals with the quantity of information in individual objects.

All the data was out there to warn us of this impending attack, why didn't we see it?

The new computing environment enabled by advances in service oriented arc- tectures, mashups, and cloud computing will consist of service spaces comprising data, applications, infrastructure resources distributed over the Web.

The six volume set LNCS 11361-11366 constitutes the proceedings of the 14th Asian Conference on Computer Vision, ACCV 2018, held in Perth, Australia, in December 2018.

The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020.

The concepts of centrality and diversity are highly important in search algorithms, and play central roles in applications of artificial intelligence (AI), machine learning (ML), social networks, and pattern recognition.

This book constitutes the refereed proceedings of five workshops and an industrial session held at the 20th International Conference on Image Analysis and Processing, ICIAP 2019, in Trento, Italy, in September 2019: Second International Workshop on Recent Advances in Digital Security: Biometrics and Forensics (BioFor 2019); First International Workshop on Pattern Recognition for Cultural  Heritage (PatReCH 2019); First International Workshop eHealth in the Big Data and Deep Learning Era (e-BADLE 2019); International Workshop on Deep Understanding Shopper Behaviors and Interactions in Intelligent Retail Environments (DEEPRETAIL 2019); Industrial Session.

Human knowledge is primarily the product of experiences acquired through interactions of our senses with our surroundings.

Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.

Multi-Modal User Interactions in Controlled Environments investigates the capture and analysis of user's multimodal behavior (mainly eye gaze, eye fixation, eye blink and body movements) within a real controlled environment (controlled-supermarket, personal environment) in order to adapt the response of the computer/environment to the user.

This book provides a general framework for repeated game playing, adaptive data compression, sequential investments, sequential pattern analysis and other problems.

The six-volume set comprising the LNCS volumes 11129-11134 constitutes the refereed proceedings of the workshops that took place in conjunction with the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.

This book constitutes the proceedings of the 12th International Workshop on Machine Learning in Medical Imaging, MLMI 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in September 2021.

The six volume set of LNCS 12622-12627 constitutes the proceedings of the 15th Asian Conference on Computer Vision, ACCV 2020, held in Kyoto, Japan, in November/ December 2020.

A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.

This contributed volume presents an overview of concepts, methods, and applications used in several quantitative areas of drug research, development, and marketing.

This updated book proposes applications of tensor decomposition to unsupervised feature extraction and feature selection.

This book constitutes refereed proceedings of the 27th International Workshop on Frontiers of Computer Vision, IW-FCV 2021, held in Daegu, South Korea, in February 2021.

A systematic description of modeling face geometry from images, including information on mathematical tools, image processing and computer vision techniques.

Updated for OpenCV 4 and Python 3, this book covers the latest on depth cameras, 3D tracking, augmented reality, and deep neural networks, helping you solve real-world computer vision problems with practical codeKey FeaturesBuild powerful computer vision applications in concise code with OpenCV 4 and Python 3Learn the fundamental concepts of image processing, object classification, and 2D and 3D trackingTrain, use, and understand machine learning models such as Support Vector Machines (SVMs) and neural networksBook DescriptionComputer vision is a rapidly evolving science, encompassing diverse applications and techniques.

Plan recognition, activity recognition, and intent recognition together combine and unify techniques from user modeling, machine vision, intelligent user interfaces, human/computer interaction, autonomous and multi-agent systems, natural language understanding, and machine learning.

This book constitutes the refereed proceedings of the 10th International Conference on Advances in Brain Inspired Cognitive Systems, BICS 2019, held in Guangzhou, China, in July 2019.

The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020.

Stereoscopic processes are increasingly used in virtual reality and entertainment.

A unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature selection, now in its second edition The art and science of combining pattern classifiers has flourished into a prolific discipline since the first edition of Combining Pattern Classifiers was published in 2004.

The Gang of Four's seminal catalog of 23 patterns to solve commonly occurring design problems Patterns allow designers to create more flexible, elegant, and ultimately reusable designs without having to rediscover the design solutions themselves.

In this book a global shape model is developed and applied to the analysis of real pictures acquired with a visible light camera under varying conditions of optical degradation.

The four-volume set LNCS 11070, 11071, 11072, and 11073 constitutes the refereed proceedings of the 21st International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018, held in Granada, Spain, in September 2018.

This book describes a range of string problems in computer science and molecular biology and the algorithms developed to solve them.

Leverage the power of Java and deep learning to build production-grade Computer Vision applications Key FeaturesBuild real-world Computer Vision applications using the power of neural networks Implement image classification, object detection, and face recognitionKnow best practices on effectively building and deploying deep learning models in JavaBook DescriptionAlthough machine learning is an exciting world to explore, you may feel confused by all of its theoretical aspects.

This book highlights research in linking and mining data from across varied data sources.

This book constitutes the proceedings of the 13th International Conference on Intelligent Robotics and Applications, ICIRA 2020, held in Kuala Lumpur, Malaysia, in November 2020.

The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020.

Delve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithmsKey FeaturesDiscover best practices for engineering and maintaining OpenCV projectsExplore important deep learning tools for image classificationUnderstand basic image matrix formats and filtersBook DescriptionOpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation.

Multidimensionalscaling(MDS)isatechniquefortheanalysisofsimilarity or dissimilarity data on a set of objects.

Pattern recognition presents one of the most significant challenges for scientists and engineers, and many different approaches have been proposed.

"e;Much of pattern recognition theory and practice, including methods such as Support Vector Machines, has emerged in an attempt to solve the character recognition problem.