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Computer Vision, Imaging and Computer Graphics Theory and Applications
This book constitutes thoroughly revised and selected papers from the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2020, held in Valletta, Malta, in February 2020. The 25 thoroughly revised and extended papers presented in this volume were carefully reviewed and selected from 455 submissions. The papers contribute to the understanding of relevant trends of current research on computer graphics; human computer interaction; information visualization; computer vision.
Computer Vision Systems
Following the highly successful International Conference on Computer Vision - stems held in Las Palmas, Spain (ICVS’99), this second International Workshop on Computer Vision Systems, ICVS 2001 was held as an associated workshop of the International Conference on Computer Vision in Vancouver, Canada. The organization of ICVS’99 and ICVS 2001 was motivated by the fact that the - jority of computer vision conferences focus on component technologies. However, Computer Vision has reached a level of maturity that allows us not only to p- form research on individual methods and system components but also to build fully integrated computer vision systems of signi cant complexity. This opens a n...
Data Visualization ’99
In the past decade visualization established its importance both in scientific research and in real-world applications. In this book 21 research papers and 9 case studies report on the latest results in volume and flow visualization and information visualization. Thus it is a valuable source of information not only for researchers but also for practitioners developing or using visualization applications.
Scalable Interactive Visualization
This book is a printed edition of the Special Issue "Scalable Interactive Visualization" that was published in Informatics
Data Science for Healthcare
This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare. Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising. This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book.
Data Abstraction and Pattern Identification in Time-series Data
Data sources such as simulations, sensor networks across many application domains generate large volumes of time-series data which exhibit characteristics that evolve over time. Visual data analysis methods can help us in exploring and understanding the underlying patterns present in time-series data but, due to their ever-increasing size, the visual data analysis process can become complex. Large data sets can be handled using data abstraction techniques by transforming the raw data into a simpler format while, at the same time, preserving significant features that are important for the user. When dealing with time-series data, abstraction techniques should also take into account the underl...
Multivariate Network Visualization
This book is the outcome of the Dagstuhl Seminar 13201 on Information Visualization - Towards Multivariate Network Visualization, held in Dagstuhl Castle, Germany in May 2013. The goal of this Dagstuhl Seminar was to bring together theoreticians and practitioners from Information Visualization, HCI and Graph Drawing with a special focus on multivariate network visualization, i.e., on graphs where the nodes and/or edges have additional (multidimensional) attributes. The integration of multivariate data into complex networks and their visual analysis is one of the big challenges not only in visualization, but also in many application areas. Thus, in order to support discussions related to the visualization of real world data, also invited researchers from selected application areas, especially bioinformatics, social sciences and software engineering. The unique "Dagstuhl climate" ensured an open and undisturbed atmosphere to discuss the state-of-the-art, new directions and open challenges of multivariate network visualization.
Mathematical Visualization
Mathematical Visualization is a young new discipline. It offers efficient visualization tools to the classical subjects of mathematics, and applies mathematical techniques to problems in computer graphics and scientific visualization. Originally, it started in the interdisciplinary area of differential geometry, numerical mathematics, and computer graphics. In recent years, the methods developed have found important applications. The current volume is the quintessence of an international workshop in September 1997 in Berlin, focusing on recent developments in this emerging area. Experts present selected research work on new algorithms for visualization problems, describe the application and experiments in geometry, and develop new numerical or computer graphical techniques.
Pattern Recognition and Computer Vision
The 4-volume set LNCS 13534, 13535, 13536 and 13537 constitutes the refereed proceedings of the 5th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2022, held in Shenzhen, China, in November 2022. The 233 full papers presented were carefully reviewed and selected from 564 submissions. The papers have been organized in the following topical sections: Theories and Feature Extraction; Machine learning, Multimedia and Multimodal; Optimization and Neural Network and Deep Learning; Biomedical Image Processing and Analysis; Pattern Classification and Clustering; 3D Computer Vision and Reconstruction, Robots and Autonomous Driving; Recognition, Remote Sensing; Vision Analysis and Understanding; Image Processing and Low-level Vision; Object Detection, Segmentation and Tracking.
Human-Computer Interaction
The pervasive influence of technology continuously shapes our daily lives. From smartphones to smart homes, technology is revolutionizing the way we live, work and interact with each other. Human-computer interaction (HCI) is a multidisciplinary research field focusing on the study of people interacting with information technology and plays a critical role in the development of computing systems that work well for the people using them, ensuring the seamless integration of interactive systems into our technologically driven lifestyles. The book series contains six volumes providing extensive coverage of the field, wherein each one addresses different theoretical and practical aspects of the ...
