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Author: Jinfeng Yang Publisher: Springer ISBN: 9811073023 Category : Computers Languages : en Pages : 630
Book Description
This three volume set, CCIS 771, 772, 773, constitutes the refereed proceedings of the CCF Chinese Conference on Computer Vision, CCCV 2017, held in Tianjin, China, in October 2017. The total of 174 revised full papers presented in three volumes were carefully reviewed and selected from 465 submissions. The papers are organized in the following topical sections: biological vision inspired visual method; biomedical image analysis; computer vision applications; deep neural network; face and posture analysis; image and video retrieval; image color and texture; image composition; image quality assessment and analysis; image restoration; image segmentation and classification; image-based modeling; object detection and classification; object identification; photography and video; robot vision; shape representation and matching; statistical methods and learning; video analysis and event recognition; visual salient detection
Author: Fouad Sabry Publisher: One Billion Knowledgeable ISBN: Category : Computers Languages : en Pages : 155
Book Description
What is Random Sample Consensus Random sample consensus, also known as RANSAC, is an iterative method that is used to estimate the parameters of a mathematical model based on a collection of observed data that includes outliers. This method is used in situations where the outliers are permitted to have no impact on the values of the estimates. The conclusion is that it is also possible to view it as a tool for detecting outliers. An algorithm is considered to be non-deterministic if it is able to generate a suitable result only with a certain probability, and this likelihood increases as the number of iterations that are permitted via the method increases. In 1981, Fischler and Bolles, who were working at SRI International, were the ones who initially published the algorithm. In order to solve the Location Determination Problem (LDP), which is a problem in which the objective is to find the points in space that project onto an image and then convert those points into a set of landmarks with known positions, they utilized RANSAC. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Random sample consensus Chapter 2: Estimator Chapter 3: Least squares Chapter 4: Outlier Chapter 5: Cross-validation (statistics) Chapter 6: Errors and residuals Chapter 7: Mixture model Chapter 8: Robust statistics Chapter 9: Image stitching Chapter 10: Resampling (statistics) (II) Answering the public top questions about random sample consensus. (III) Real world examples for the usage of random sample consensus in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Random Sample Consensus.
Author: Tat-Jun Chin Publisher: Morgan & Claypool Publishers ISBN: 1627052860 Category : Computers Languages : en Pages : 196
Book Description
Outlier-contaminated data is a fact of life in computer vision. For computer vision applications to perform reliably and accurately in practical settings, the processing of the input data must be conducted in a robust manner. In this context, the maximum consensus robust criterion plays a critical role by allowing the quantity of interest to be estimated from noisy and outlier-prone visual measurements. The maximum consensus problem refers to the problem of optimizing the quantity of interest according to the maximum consensus criterion. This book provides an overview of the algorithms for performing this optimization. The emphasis is on the basic operation or "inner workings" of the algorithms, and on their mathematical characteristics in terms of optimality and efficiency. The applicability of the techniques to common computer vision tasks is also highlighted. By collecting existing techniques in a single article, this book aims to trigger further developments in this theoretically interesting and practically important area.
Author: Giuseppe Bonaccorso Publisher: Packt Publishing Ltd ISBN: 1785884514 Category : Computers Languages : en Pages : 352
Book Description
Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation. Get a solid foundation for your entry into Machine Learning by strengthening your roots (algorithms) with this comprehensive guide. Who This Book Is For This book is for IT professionals who want to enter the field of data science and are very new to Machine Learning. Familiarity with languages such as R and Python will be invaluable here. What You Will Learn Acquaint yourself with important elements of Machine Learning Understand the feature selection and feature engineering process Assess performance and error trade-offs for Linear Regression Build a data model and understand how it works by using different types of algorithm Learn to tune the parameters of Support Vector machines Implement clusters to a dataset Explore the concept of Natural Processing Language and Recommendation Systems Create a ML architecture from scratch. In Detail As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. In this book you will learn all the important Machine Learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naive Bayes, K-Means, Random Forest, TensorFlow, and Feature engineering. In this book you will also learn how these algorithms work and their practical implementation to resolve your problems. This book will also introduce you to the Natural Processing Language and Recommendation systems, which help you run multiple algorithms simultaneously. On completion of the book you will have mastered selecting Machine Learning algorithms for clustering, classification, or regression based on for your problem. Style and approach An easy-to-follow, step-by-step guide that will help you get to grips with real -world applications of Algorithms for Machine Learning.
Author: Anders Heyden Publisher: Springer ISBN: 9783540437451 Category : Computers Languages : en Pages : 820
Book Description
Premiering in 1990 in Antibes, France, the European Conference on Computer Vision, ECCV, has been held biennially at venues all around Europe. These conferences have been very successful, making ECCV a major event to the computer vision community. ECCV 2002 was the seventh in the series. The privilege of organizing it was shared by three universities: The IT University of Copenhagen, the University of Copenhagen, and Lund University, with the conference venue in Copenhagen. These universities lie ̈ geographically close in the vivid Oresund region, which lies partly in Denmark and partly in Sweden, with the newly built bridge (opened summer 2000) crossing the sound that formerly divided the countries. We are very happy to report that this year’s conference attracted more papers than ever before, with around 600 submissions. Still, together with the conference board, we decided to keep the tradition of holding ECCV as a single track conference. Each paper was anonymously refereed by three different reviewers. For the ?nal selection, for the ?rst time for ECCV, a system with area chairs was used. These met with the program chairsinLundfortwodaysinFebruary2002toselectwhatbecame45oralpresentations and 181 posters.Also at this meeting the selection was made without knowledge of the authors’identity.
Author: Joong Hoon Kim Publisher: Springer ISBN: 3662479265 Category : Computers Languages : en Pages : 456
Book Description
The Harmony Search Algorithm (HSA) is one of the most well-known techniques in the field of soft computing, an important paradigm in the science and engineering community. This volume, the proceedings of the 2nd International Conference on Harmony Search Algorithm 2015 (ICHSA 2015), brings together contributions describing the latest developments in the field of soft computing with a special focus on HSA techniques. It includes coverage of new methods that have potentially immense application in various fields. Contributed articles cover aspects of the following topics related to the Harmony Search Algorithm: analytical studies; improved, hybrid and multi-objective variants; parameter tuning; and large-scale applications. The book also contains papers discussing recent advances on the following topics: genetic algorithms; evolutionary strategies; the firefly algorithm and cuckoo search; particle swarm optimization and ant colony optimization; simulated annealing; and local search techniques. This book offers a valuable snapshot of the current status of the Harmony Search Algorithm and related techniques, and will be a useful reference for practising researchers and advanced students in computer science and engineering.
Author: Anis Koubaa Publisher: Springer Nature ISBN: 3030779394 Category : Technology & Engineering Languages : en Pages : 731
Book Description
This book is used at the graduate or advanced undergraduate level and many others. Manned and unmanned ground, aerial and marine vehicles enable many promising and revolutionary civilian and military applications that will change our life in the near future. These applications include, but are not limited to, surveillance, search and rescue, environment monitoring, infrastructure monitoring, self-driving cars, contactless last-mile delivery vehicles, autonomous ships, precision agriculture and transmission line inspection to name just a few. These vehicles will benefit from advances of deep learning as a subfield of machine learning able to endow these vehicles with different capability such as perception, situation awareness, planning and intelligent control. Deep learning models also have the ability to generate actionable insights into the complex structures of large data sets. In recent years, deep learning research has received an increasing amount of attention from researchers in academia, government laboratories and industry. These research activities have borne some fruit in tackling some of the challenging problems of manned and unmanned ground, aerial and marine vehicles that are still open. Moreover, deep learning methods have been recently actively developed in other areas of machine learning, including reinforcement training and transfer/meta-learning, whereas standard, deep learning methods such as recent neural network (RNN) and coevolutionary neural networks (CNN). The book is primarily meant for researchers from academia and industry, who are working on in the research areas such as engineering, control engineering, robotics, mechatronics, biomedical engineering, mechanical engineering and computer science. The book chapters deal with the recent research problems in the areas of reinforcement learning-based control of UAVs and deep learning for unmanned aerial systems (UAS) The book chapters present various techniques of deep learning for robotic applications. The book chapters contain a good literature survey with a long list of references. The book chapters are well written with a good exposition of the research problem, methodology, block diagrams and mathematical techniques. The book chapters are lucidly illustrated with numerical examples and simulations. The book chapters discuss details of applications and future research areas.
Author: Bashar Alsadik Publisher: Elsevier ISBN: 0128175893 Category : Science Languages : en Pages : 426
Book Description
Adjustment Models in 3D Geomatics and Computational Geophysics: With MATLAB Examples, Volume Four introduces a complete package of theoretical and practical subjects in adjustment computations relating to Geomatics and geophysical applications, particularly photogrammetry, surveying, remote sensing, GIS, cartography, and geodesy. Supported by illustrating figures and solved examples with MATLAB codes, the book provides clear methods for processing 3D data for accurate and reliable results. Problems cover free net adjustment, adjustment with constraints, blunder detection, RANSAC, robust estimation, error propagation, 3D co-registration, image pose determination, and more. - Covers both the theory and practice of using adjustment techniques in a wide variety of modern applications in Geomatics - Presents topics on the Kalman filter, Robust estimation, Levenberg Marquardt technique, and many other vital applications in the context of Geomatics and photogrammetry - Provides 75 solved problems in detail, especially related to 3-dimensional applications of Geomatics - Offers MATLAB codes to strengthen understanding and give readers up-to-date knowledge on information science
Author: Weidong Chen Publisher: Springer ISBN: 3319480367 Category : Technology & Engineering Languages : en Pages : 1118
Book Description
This book describes the latest research advances, innovations, and visions in the field of robotics as presented by leading researchers, engineers, and practitioners from around the world at the 14th International Conference on Intelligent Autonomous Systems (IAS-14), held in Shanghai, China in July 2016. The contributions amply demonstrate that robots, machines and systems are rapidly achieving intelligence and autonomy, attaining more and more capabilities such as mobility and manipulation, sensing and perception, reasoning, and decision-making. They cover a wide range of research results and applications, and particular attention is paid to the emerging role of autonomous robots and intelligent systems in industrial production, which reflects their maturity and robustness. The contributions were selected by means of a rigorous peer-review process and highlight many exciting and visionary ideas that will further galvanize the research community and spur novel research directions. The series of biennial IAS conferences, which began in 1986, represents a premiere event in the field of robotics.
Author: Shichang Du Publisher: Springer Nature ISBN: 981150279X Category : Technology & Engineering Languages : en Pages : 338
Book Description
This book provides insights into surface quality control techniques and applications based on high-definition metrology (HDM). Intended as a reference resource for engineers who routinely use a variety of quality control methods and are interested in understanding the data processing, from HDM data to final control actions, it can also be used as a textbook for advanced courses in engineering quality control applications for students who are already familiar with quality control methods and practices. It enables readers to not only assimilate the quality control methods involved, but also to quickly implement the techniques in practical engineering problems. Further, it includes numerous case studies to highlight the implementation of the methods using measured HDM data of surface features. Since MATLAB is extensively employed in these case studies, familiarity with this software is helpful, as is a general understanding of surface quality control methods.
Author: Jinfeng Yang
Author: Fouad Sabry
Author: Tat-Jun Chin
Author: Giuseppe Bonaccorso
Author: Anders Heyden
Author: Joong Hoon Kim
Author: Anis Koubaa
Author: Bashar Alsadik
Author: Weidong Chen
Author: Shichang Du
Author: Álvaro Rocha