We surveyed a set of SOM-based works illustrating, as we consider, innovative visualization approaches and application concepts. We argued that while the base SOM algorithm is already well-known and widely used, much innovation potential exists in further improving SOM visualization and defining novel application areas. Specifically, the Information Visualization field offers a rich background of visualization approaches which can be exploited for advanced SOM visualization. Deeper application integration and visual-interactive control of the SOM training process are regarded promising for future applications. The tight integration of automatic data analysis and visualization, as demonstrated by many SOM-based systems, offers much potential in handling increasing amounts of complex data, and is considered a promising basis for efficient information retrieval systems.

th This two-volume set constitutes the Proceedings of the 16 International Conference on Neural Information Processing (ICONIP 2009), held in Bangkok, Thailand, during December 1–5, 2009. ICONIP is a world-renowned international conference that is held annually in the Asia-Pacific region. This prestigious event is sponsored by the Asia Pacific Neural Network Assembly (APNNA), and it has provided an annual forum for international researchers to exchange the latest ideas and advances in neural networks and related discipline. The School of Information Technology (SIT) at King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand was the proud host of ICONIP 2009. The conference theme was “Challenges and Trends of Neural Information Processing,” with an aim to discuss the past, present, and future challenges and trends in the field of neural information processing. ICONIP 2009 accepted 145 regular session papers and 53 special session papers from a total of 466 submissions received on the Springer Online Conference Service (OCS) system. The authors of accepted papers alone covered 36 countries and - gions worldwide and there are over 500 authors in these proceedings. The technical sessions were divided into 23 topical categories, including 9 special sessions.

This book constitutes the refereed proceedings of the 6th International Conference on Image Analysis and Recognition, ICIAR 2009, held in Halifax, Canada, in July 2009. The 93 revised full papers presented were carefully reviewed and selected from 164 submissions. The papers are organized in topical sections on image and video processing and analysis; image segmentation; image and video retrieval and indexing; pattern analysis and recognition; biometrics face recognition; shape analysis; motion analysis and tracking; 3D image analysis; biomedical image analysis; document analysis and applications.

This book is an extended collection of contributions that wereoriginally subm- ted to the 1st International Workshop on Adaptive Multimedia Retrieval (AMR 2003), which was organized as part of the 26th German Conference on Arti?cial Intelligence (KI 2003),and held during September 15–18,2003at the University of Hamburg, Germany. Motivated by the overall success of the workshop – as revealed by the stimulating atmosphere during the workshop and the number of very interested and active participants – we ?nally decided to edit a book based on revised papers that were initially submitted to the workshop. Furthermore, we invited some more introductory contributions in order to be able to provide a conclusive book on current topics in the area of adaptive multimedia retrieval systems. We hope that we were able to put together a stimulating collection of articles for the interested reader. We like to thank the organizationcommittee of the 26th German Conference on Arti?cial Intelligence (KI 2003) for providing the setting and the admin- trative support in realizing this workshop as part of their program. Especially, we like to thank Christopher Habel for promoting the workshop as part of the conference program and Andreas Gun ̈ ther for his kind support throughout the organization process.

In the age of big data, being able to make sense of data is an important key to success. Interactive Visual Data Analysis advocates the synthesis of visualization, interaction, and automatic computation to facilitate insight generation and knowledge crystallization from large and complex data. The book provides a systematic and comprehensive overview of visual, interactive, and analytical methods. It introduces criteria for designing interactive visual data analysis solutions, discusses factors influencing the design, and examines the involved processes. The reader is made familiar with the basics of visual encoding and gets to know numerous visualization techniques for multivariate data, temporal data, geo-spatial data, and graph data. A dedicated chapter introduces general concepts for interacting with visualizations and illustrates how modern interaction technology can facilitate the visual data analysis in many ways. Addressing today’s large and complex data, the book covers relevant automatic analytical computations to support the visual data analysis. The book also sheds light on advanced concepts for visualization in multi-display environments, user guidance during the data analysis, and progressive visual data analysis. The authors present a top-down perspective on interactive visual data analysis with a focus on concise and clean terminology. Many real-world examples and rich illustrations make the book accessible to a broad interdisciplinary audience from students, to experts in the field, to practitioners in data-intensive application domains. Features: Dedicated to the synthesis of visual, interactive, and analysis methods Systematic top-down view on visualization, interaction, and automatic analysis Broad coverage of fundamental and advanced visualization techniques Comprehensive chapter on interacting with visual representations Extensive integration of automatic computational methods Accessible portrayal of cutting-edge visual analytics technology Foreword by Jack van Wijk For more information, you can also visit the author website, where the book's figures are made available under the CC BY Open Access license.

A timely overview of cutting edge technologies for multimedia retrieval with a special emphasis on scalability The amount of multimedia data available every day is enormous and is growing at an exponential rate, creating a great need for new and more efficient approaches for large scale multimedia search. This book addresses that need, covering the area of multimedia retrieval and placing a special emphasis on scalability. It reports the recent works in large scale multimedia search, including research methods and applications, and is structured so that readers with basic knowledge can grasp the core message while still allowing experts and specialists to drill further down into the analytical sections. Big Data Analytics for Large-Scale Multimedia Search covers: representation learning, concept and event-based video search in large collections; big data multimedia mining, large scale video understanding, big multimedia data fusion, large-scale social multimedia analysis, privacy and audiovisual content, data storage and management for big multimedia, large scale multimedia search, multimedia tagging using deep learning, interactive interfaces for big multimedia and medical decision support applications using large multimodal data. Addresses the area of multimedia retrieval and pays close attention to the issue of scalability Presents problem driven techniques with solutions that are demonstrated through realistic case studies and user scenarios Includes tables, illustrations, and figures Offers a Wiley-hosted BCS that features links to open source algorithms, data sets and tools Big Data Analytics for Large-Scale Multimedia Search is an excellent book for academics, industrial researchers, and developers interested in big multimedia data search retrieval. It will also appeal to consultants in computer science problems and professionals in the multimedia industry.

Finally,wearegrateful tooursponsors,theBritishComputerSocietyInformationRetrievalSpecialist Group,theBritishMachineVisionAssociation(BMVA),theInstituteforImage DataResearch,UniversityofNorthumbria,theInstitutionofElectricalEn- neers(IEE),andtheLeidenInstituteofAdvancedComputerScience(LIACS), LeidenUniversiy. May2002 MichaelS. Lew NicuSebe JohnP. Eakins International Conference an Image andVideo Retrieval 2002 Organization Organizing Committee OrganizingCommitteeChair: JohnP. Eakins (UniversityofNorthumbria,UK) TechnicalProgramChair: MichaelS.

Here are the refereed proceedings of the 5th International Conference on Image and Video Retrieval, CIVR 2006, held in Singapore in July 2006. Presents 18 revised full papers and 30 poster papers, together with extended abstracts of 5 papers of 1 special session and those of 10 demonstration papers. These cover interactive image and video retrieval, semantic image retrieval, visual feature analysis, learning and classification, image and video retrieval metrics, and machine tagging.