Bridging the semantic gap in image and video analysis / volume 145

Saved in:
Bibliographic Details
Imprint:Cham, Switzerland : Springer, 2018.
Description:1 online resource (x, 163 pages) : illustrations (some color)
Series:Intelligent systems reference library, 1868-4394 ; volume 145
Intelligent systems reference library ; v. 145.
Subject:Semantic computing.
Image analysis.
COMPUTERS -- General.
Semantics, discourse analysis, etc.
Artificial intelligence.
Imaging systems & technology.
Image processing.
Image analysis.
Semantic computing.
Electronic books.
Format: E-Resource Book
URL for this record:
Hidden Bibliographic Details
Other authors / contributors:Kwaśnicka, Halina, editor.
Jain, L. C., editor.
Digital file characteristics:text file PDF
Notes:Includes bibliographical references and index.
Online resource; title from PDF title page (SpringerLink, viewed February 27, 2018).
Summary:This book presents cutting-edge research on various ways to bridge the semantic gap in image and video analysis. The respective chapters address different stages of image processing, revealing that the first step is a future extraction, the second is a segmentation process, the third is object recognition, and the fourth and last involve the semantic interpretation of the image. The semantic gap is a challenging area of research, and describes the difference between low-level features extracted from the image and the high-level semantic meanings that people can derive from the image. The result greatly depends on lower level vision techniques, such as feature selection, segmentation, object recognition, and so on. The use of deep models has freed humans from manually selecting and extracting the set of features. Deep learning does this automatically, developing more abstract features at the successive levels. The book offers a valuable resource for researchers, practitioners, students and professors in Computer Engineering, Computer Science and related fields whose work involves images, video analysis, image interpretation and so on.
Other form:Print version: 3319738909 9783319738901
Standard no.:10.1007/978-3-319-73891-8