[PDF] Color Based And Gradient Based Object Tracking Using Particle Filter Embedded In Incremental Discriminant Model - eBooks Review

Color Based And Gradient Based Object Tracking Using Particle Filter Embedded In Incremental Discriminant Model


Color Based And Gradient Based Object Tracking Using Particle Filter Embedded In Incremental Discriminant Model
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Download Color Based And Gradient Based Object Tracking Using Particle Filter Embedded In Incremental Discriminant Model PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Color Based And Gradient Based Object Tracking Using Particle Filter Embedded In Incremental Discriminant Model book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page





Color Based And Gradient Based Object Tracking Using Particle Filter Embedded In Incremental Discriminant Model


Color Based And Gradient Based Object Tracking Using Particle Filter Embedded In Incremental Discriminant Model
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Author : 黃彥淇
language : en
Publisher:
Release Date : 2008

Color Based And Gradient Based Object Tracking Using Particle Filter Embedded In Incremental Discriminant Model written by 黃彥淇 and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.




Object Tracking Based On Color Information Employing Particle Filter Algorithm


Object Tracking Based On Color Information Employing Particle Filter Algorithm
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Author : Budi Sugandi
language : en
Publisher:
Release Date : 2011

Object Tracking Based On Color Information Employing Particle Filter Algorithm written by Budi Sugandi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.




Artificial Intelligence In Healthcare


Artificial Intelligence In Healthcare
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Author : Adam Bohr
language : en
Publisher: Academic Press
Release Date : 2020-06-21

Artificial Intelligence In Healthcare written by Adam Bohr and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-21 with Computers categories.


Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data



Visual Object Recognition


Visual Object Recognition
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Author : Kristen Thielscher
language : en
Publisher: Springer Nature
Release Date : 2022-05-31

Visual Object Recognition written by Kristen Thielscher and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.


The visual recognition problem is central to computer vision research. From robotics to information retrieval, many desired applications demand the ability to identify and localize categories, places, and objects. This tutorial overviews computer vision algorithms for visual object recognition and image classification. We introduce primary representations and learning approaches, with an emphasis on recent advances in the field. The target audience consists of researchers or students working in AI, robotics, or vision who would like to understand what methods and representations are available for these problems. This lecture summarizes what is and isn't possible to do reliably today, and overviews key concepts that could be employed in systems requiring visual categorization. Table of Contents: Introduction / Overview: Recognition of Specific Objects / Local Features: Detection and Description / Matching Local Features / Geometric Verification of Matched Features / Example Systems: Specific-Object Recognition / Overview: Recognition of Generic Object Categories / Representations for Object Categories / Generic Object Detection: Finding and Scoring Candidates / Learning Generic Object Category Models / Example Systems: Generic Object Recognition / Other Considerations and Current Challenges / Conclusions



Conformal Prediction For Reliable Machine Learning


Conformal Prediction For Reliable Machine Learning
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Author : Vineeth Balasubramanian
language : en
Publisher: Newnes
Release Date : 2014-04-23

Conformal Prediction For Reliable Machine Learning written by Vineeth Balasubramanian and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-23 with Computers categories.


The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detection. As practitioners and researchers around the world apply and adapt the framework, this edited volume brings together these bodies of work, providing a springboard for further research as well as a handbook for application in real-world problems. Understand the theoretical foundations of this important framework that can provide a reliable measure of confidence with predictions in machine learning Be able to apply this framework to real-world problems in different machine learning settings, including classification, regression, and clustering Learn effective ways of adapting the framework to newer problem settings, such as active learning, model selection, or change detection



Video Analytics For Business Intelligence


Video Analytics For Business Intelligence
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Author : Caifeng Shan
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-04-07

Video Analytics For Business Intelligence written by Caifeng Shan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-07 with Computers categories.


Closed Circuit TeleVision (CCTV) cameras have been increasingly deployed pervasively in public spaces including retail centres and shopping malls. Intelligent video analytics aims to automatically analyze content of massive amount of public space video data and has been one of the most active areas of computer vision research in the last two decades. Current focus of video analytics research has been largely on detecting alarm events and abnormal behaviours for public safety and security applications. However, increasingly CCTV installations have also been exploited for gathering and analyzing business intelligence information, in order to enhance marketing and operational efficiency. For example, in retail environments, surveillance cameras can be utilised to collect statistical information about shopping behaviour and preference for marketing (e.g., how many people entered a shop; how many females/males or which age groups of people showed interests to a particular product; how long did they stay in the shop; and what are the frequent paths), and to measure operational efficiency for improving customer experience. Video analytics has the enormous potential for non-security oriented commercial applications. This book presents the latest developments on video analytics for business intelligence applications. It provides both academic and commercial practitioners an understanding of the state-of-the-art and a resource for potential applications and successful practice.



Human Robot Interaction


Human Robot Interaction
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Author : Gholamreza Anbarjafari
language : en
Publisher: BoD – Books on Demand
Release Date : 2018-07-04

Human Robot Interaction written by Gholamreza Anbarjafari and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-04 with Computers categories.


This book takes the vocal and visual modalities and human-robot interaction applications into account by considering three main aspects, namely, social and affective robotics, robot navigation, and risk event recognition. This book can be a very good starting point for the scientists who are about to start their research work in the field of human-robot interaction.



Visual Object Tracking From Correlation Filter To Deep Learning


Visual Object Tracking From Correlation Filter To Deep Learning
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Author : Weiwei Xing
language : en
Publisher: Springer Nature
Release Date : 2021-11-18

Visual Object Tracking From Correlation Filter To Deep Learning written by Weiwei Xing and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-18 with Computers categories.


The book focuses on visual object tracking systems and approaches based on correlation filter and deep learning. Both foundations and implementations have been addressed. The algorithm, system design and performance evaluation have been explored for three kinds of tracking methods including correlation filter based methods, correlation filter with deep feature based methods, and deep learning based methods. Firstly, context aware and multi-scale strategy are presented in correlation filter based trackers; then, long-short term correlation filter, context aware correlation filter and auxiliary relocation in SiamFC framework are proposed for combining correlation filter and deep learning in visual object tracking; finally, improvements in deep learning based trackers including Siamese network, GAN and reinforcement learning are designed. The goal of this book is to bring, in a timely fashion, the latest advances and developments in visual object tracking, especially correlation filter and deep learning based methods, which is particularly suited for readers who are interested in the research and technology innovation in visual object tracking and related fields.



Handbook Of Medical Image Computing And Computer Assisted Intervention


Handbook Of Medical Image Computing And Computer Assisted Intervention
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Author : S. Kevin Zhou
language : en
Publisher: Academic Press
Release Date : 2019-10-18

Handbook Of Medical Image Computing And Computer Assisted Intervention written by S. Kevin Zhou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-18 with Computers categories.


Handbook of Medical Image Computing and Computer Assisted Intervention presents important advanced methods and state-of-the art research in medical image computing and computer assisted intervention, providing a comprehensive reference on current technical approaches and solutions, while also offering proven algorithms for a variety of essential medical imaging applications. This book is written primarily for university researchers, graduate students and professional practitioners (assuming an elementary level of linear algebra, probability and statistics, and signal processing) working on medical image computing and computer assisted intervention. Presents the key research challenges in medical image computing and computer-assisted intervention Written by leading authorities of the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society Contains state-of-the-art technical approaches to key challenges Demonstrates proven algorithms for a whole range of essential medical imaging applications Includes source codes for use in a plug-and-play manner Embraces future directions in the fields of medical image computing and computer-assisted intervention



Automated Machine Learning


Automated Machine Learning
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Author : Frank Hutter
language : en
Publisher: Springer
Release Date : 2019-05-17

Automated Machine Learning written by Frank Hutter and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-17 with Computers categories.


This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.