Subspace, Latent Structure and Feature Selection


Book Description

This book constitutes the thoroughly refereed post-proceedings of the PASCAL (pattern analysis, statistical modelling and computational learning) Statistical and Optimization Perspectives Workshop on Subspace, Latent Structure and Feature Selection techniques, SLSFS 2005. The 9 revised full papers presented together with 5 invited papers reflect the key approaches that have been developed for subspace identification and feature selection using dimension reduction techniques, subspace methods, random projection methods, among others.




Pattern Recognition


Book Description

This book constitutes the refereed proceedings of the 31st Symposium of the German Association for Pattern Recognition, DAGM 2009, held in Jena, Germany, in September 2009. The 56 revised full papers were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on motion and tracking; pedestrian recognition and automotive applications; features; single-view and 3D reconstruction; learning and classification; pattern recognition and estimation; stereo and multi-view reconstruction; image analysis and applications; and segmentation.




4th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2007)


Book Description

This book contains papers from the International Workshop on Wearable and Implantable Body Sensor Networks, BSN 2007, held in March 2007 at the University Hospital Aachen, Germany. Topics covered in the volume include new medical measurements, smart bio-sensing textiles, low-power wireless networking, system integration, medical signal processing, multi-sensor data fusion, and on-going standardization activities.




Handbook of Statistical Bioinformatics


Book Description

Numerous fascinating breakthroughs in biotechnology have generated large volumes and diverse types of high throughput data that demand the development of efficient and appropriate tools in computational statistics integrated with biological knowledge and computational algorithms. This volume collects contributed chapters from leading researchers to survey the many active research topics and promote the visibility of this research area. This volume is intended to provide an introductory and reference book for students and researchers who are interested in the recent developments of computational statistics in computational biology.




Advances in Intelligent Decision Technologies


Book Description

Intelligent Decision Technologies (IDT) seeks an interchange of research on intelligent systems and intelligent technologies which enhance or improve decision making in industry, government and academia. The focus is interdisciplinary in nature, and includes research on all aspects of intelligent decision technologies, from fundamental development to the applied system. This volume represents leading research from the Second KES International Symposium on Intelligent Decision Technologies (KES IDT’10), hosted and organized by the Sellinger School of Business and Management, Loyola University Maryland, USA, in conjunction with KES International. The symposium was concerned with theory, design development, implementation, testing and evaluation of intelligent decision systems. Topics include decision making theory, intelligent agents, fuzzy logic, multi-agent systems, Bayesian networks, optimization, artificial neural networks, genetic algorithms, expert systems, decision support systems, geographic information systems, case-based reasoning, time series, knowledge management systems, Kansei communication, rough sets, spatial decision analysis, and multi-criteria decision analysis. These technologies have the potential to revolutionize decision making in many areas of management, healthcare, international business, finance, accounting, marketing, military applications, ecommerce, network management, crisis response, building design, information retrieval, and disaster recovery.




Learning to Understand Remote Sensing Images


Book Description

With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.




Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques


Book Description

"This book is a timely compendium of key elements that are crucial for the study of machine learning in chemoinformatics, giving an overview of current research in machine learning and their applications to chemoinformatics tasks"--Provided by publisher.




Big Data Analytics in Chemoinformatics and Bioinformatics


Book Description

Big Data Analytics in Chemoinformatics and Bioinformatics: With Applications to Computer-Aided Drug Design, Cancer Biology, Emerging Pathogens and Computational Toxicology provides an up-to-date presentation of big data analytics methods and their applications in diverse fields. The proper management of big data for decision-making in scientific and social issues is of paramount importance. This book gives researchers the tools they need to solve big data problems in these fields. It begins with a section on general topics that all readers will find useful and continues with specific sections covering a range of interdisciplinary applications. Here, an international team of leading experts review their respective fields and present their latest research findings, with case studies used throughout to analyze and present key information. - Brings together the current knowledge on the most important aspects of big data, including analysis using deep learning and fuzzy logic, transparency and data protection, disparate data analytics, and scalability of the big data domain - Covers many applications of big data analysis in diverse fields such as chemistry, chemoinformatics, bioinformatics, computer-assisted drug/vaccine design, characterization of emerging pathogens, and environmental protection - Highlights the considerable benefits offered by big data analytics to science, in biomedical fields and in industry




Web Information Systems - WISE 2006 Workshops


Book Description

This book constitutes the joint refereed proceedings of the three workshops held in conjunction with the 7th International Conference on Web Information Systems, WISE 2006, in Wuhan, China, in October 2006.




Emerging Sensor Technology in Agriculture


Book Description

Digital agriculture is gaining traction among scientists implementing different new and emerging sensor technologies to monitor complex soil–plant–atmosphere interactions in an accurate, cost-effective and user-friendly manner. This book presents some of the latest advances in this emerging area of research. The diversity of applications in which digital agriculture can make an important difference in day-to-day farming decision making makes this discipline an important focus of research internationally.