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Computer Vision and Pattern Recognition in Environmental Informatics

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by Jun Zhou
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Computer Vision and Pattern Recognition in Environmental Informatics by Jun Zhou

Computer Vision and Pattern Recognition (CVPR) together play an important role in the processes involved in environmental informatics due to their pervasive, non-destructive, effective, and efficient natures. As a result, CVPR has made significant contributions to the field of environmental informatics by enabling multi-modal data fusion and feature extraction, supporting fast and reliable object detection and classification, and mining the intrinsic relationship between different aspects of environmental data. Computer Vision and Pattern Recognition in Environmental Informatics describes a number of methods and tools for image interpretation and analysis, which enables observation, modelling, and understanding of environmental targets. In addition to case studies on monitoring and modeling plant, soil, insect, and aquatic animals, this publication includes discussions on innovative new ideas related to environmental monitoring, automatic fish segmentation and recognition, real-time motion tracking systems, sparse coding and decision fusion, and cell phone image-based classification and provides useful references for professionals, researchers, engineers, and students with various backgrounds within a multitude of communities.

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Ebook Details
Pages: 408
Size: 27.1 MB
Publisher: Information Science Reference
Date published:   2015
ISBN: 9781466694361 (DRM-PDF)

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This product is listed in the following categories:

Nonfiction > Computers > Computer Vision
Nonfiction > Technology > Environmental
Nonfiction > Science > Environmental Science

This author has products in the following categories:

Nonfiction > Computers > Computer Vision
Nonfiction > Technology > Environmental
Nonfiction > Science > Environmental Science
Nonfiction > Political Science > Public Policy > Economic Policy
Nonfiction > History > Asia > China
Nonfiction > Political Science > Labor & Industrial Relations

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03/24/2017
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