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Video Object Segmentation
  • Language: en
  • Pages: 194

Video Object Segmentation

This book provides a thorough overview of recent progress in video object segmentation, providing researchers and industrial practitioners with thorough information on the most important problems and developed technologies in the area. Video segmentation is a fundamental topic for video understanding in computer vision. Segmenting unique objects in a given video is useful for a variety of applications, including video conference, video editing, surveillance, and autonomous driving. Given the revolution of deep learning in computer vision problems, numerous new tasks, datasets, and methods have been recently proposed in the domain of segmentation. The book includes these recent results and findings in large-scale video object segmentation as well as benchmarks in large-scale human-centric video analysis in complex events. The authors provide readers with a comprehensive understanding of the challenges involved in video object segmentation, as well as the most effective methods for resolving them.

Computer Vision -- ECCV 2014
  • Language: en
  • Pages: 855

Computer Vision -- ECCV 2014

  • Type: Book
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  • Published: 2014-08-14
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  • Publisher: Springer

The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 363 revised papers presented were carefully reviewed and selected from 1444 submissions. The papers are organized in topical sections on tracking and activity recognition; recognition; learning and inference; structure from motion and feature matching; computational photography and low-level vision; vision; segmentation and saliency; context and 3D scenes; motion and 3D scene analysis; and poster sessions.

Computer Vision – ECCV 2016
  • Language: en
  • Pages: 893

Computer Vision – ECCV 2016

  • Type: Book
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  • Published: 2016-09-15
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  • Publisher: Springer

The eight-volume set comprising LNCS volumes 9905-9912 constitutes the refereed proceedings of the 14th European Conference on Computer Vision, ECCV 2016, held in Amsterdam, The Netherlands, in October 2016. The 415 revised papers presented were carefully reviewed and selected from 1480 submissions. The papers cover all aspects of computer vision and pattern recognition such as 3D computer vision; computational photography, sensing and display; face and gesture; low-level vision and image processing; motion and tracking; optimization methods; physics-based vision, photometry and shape-from-X; recognition: detection, categorization, indexing, matching; segmentation, grouping and shape representation; statistical methods and learning; video: events, activities and surveillance; applications. They are organized in topical sections on detection, recognition and retrieval; scene understanding; optimization; image and video processing; learning; action, activity and tracking; 3D; and 9 poster sessions.

ECAI 2020
  • Language: en
  • Pages: 3122

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 ...

Report of State Officers, Board and Committees to the General Assembly of the State of South Carolina
  • Language: en
  • Pages: 1588
Machine Learning
  • Language: en
  • Pages: 1102

Machine Learning

  • Type: Book
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  • Published: 2012-08-24
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  • Publisher: MIT Press

A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach. Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developm...

Annual Report of the South Carolina Tax Commission to the Governor and General Assembly
  • Language: en
  • Pages: 298
SPE Reservoir Evaluation & Engineering
  • Language: en
  • Pages: 618

SPE Reservoir Evaluation & Engineering

  • Type: Book
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  • Published: 1999
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  • Publisher: Unknown

None

General Catalog
  • Language: en
  • Pages: 124

General Catalog

  • Type: Book
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  • Published: 1898
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  • Publisher: Unknown

None

Proceedings of the Common Council of the City of Buffalo, ...
  • Language: en
  • Pages: 2392

Proceedings of the Common Council of the City of Buffalo, ...

  • Type: Book
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  • Published: 1900
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  • Publisher: Unknown

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