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Machine Learning and Knowledge Discovery in Databases
This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2009, held in Bled, Slovenia, in September 2009. The 106 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 422 paper submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
Video Object Tracking
This book provides a thorough overview of recent progress in video object tracking, allowing researchers and industrial practitioners to gain a better understanding of the most important problems and developed technologies in the area. Video tracking is a key research area in computer vision and aims to track unique objects in a given video, which are useful for various applications such as video conference, video editing, surveillance, and autonomous driving. This book begins with an introduction to the task of video object tracking, including the most common problem settings. Given the revolution of deep learning in computer vision problems, numerous new tasks, datasets, and methods have been recently proposed in the domain of video tracking. The book includes these recent results as well as benchmarks in large-scale human-centric video analysis in complex events.
ECAI 2020
This book presents the proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020), held in Santiago de Compostela, Spain, from 29 August to 8 September 2020. The conference was postponed from June, and much of it conducted online due to the COVID-19 restrictions. The conference is one of the principal occasions for researchers and practitioners of AI to meet and discuss the latest trends and challenges in all fields of AI and to demonstrate innovative applications and uses of advanced AI technology. The book also includes the proceedings of the 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020) held at the same time. A record number of ...
Data Classification
Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification: Algorithms and Applications explores the underlyi
Theoretical Aspects of Neural Computation: A Multidisciplinary Perspective
Over the past decade or so, neural computation has emerged as a research area with active involvement by researchers from a number of different disciplines, including computer science, engineering, mathematics, neurobiology, physics, and statistics. The workshop brought together researchers with a diverse background to review the current status of neural computation research. Three aspects of neural computation have been emphasized: neuroscience aspects, computational and Mathematical aspects, and statistical physics aspects. This book contains 28 contributions from frontier researchers in these fields. Thoroughly re-edited, and in some cases revised post-workshop, these papers collated into this review volume provide a top-class reference summary of the state-of-the-art work done in this field.
Image Analysis Applications and Computer Graphics
When scheduling involves batching decisions as well, e. g. in the presence of (sequence dependent) setup times, difficult problems arise. The book presents a problem classification in the area of batching (including multi-level and parallel machine problems) and develops several exact and heuristic algorithms to solve them. Special attention is given to the discrete lotsizing and scheduling problem which turns out to be a special batching and scheduling problem in this context. The book also contains a comparison of constraint (logic) programming with mixed-integer programming solvers for batching problems.
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