Bridging the Semantic Gap in Image and Video Analysis

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 recog...

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Detaylı Bibliyografya
Müşterek Yazar: SpringerLink (Online service)
Diğer Yazarlar: Kwaśnicka, Halina (Editör), Jain, Lakhmi C. (Editör)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer International Publishing : 2018.
Imprint: Springer,
Edisyon:1st ed. 2018.
Seri Bilgileri:Intelligent Systems Reference Library, 145
Konular:
Computational intelligence.
Semiotics.
Artificial intelligence.
Signal processing.
Computer vision.
Computational Intelligence.
Artificial Intelligence.
Signal, Speech and Image Processing.
Computer Vision.
Online Erişim:Full-text access
İçindekiler:
  • Semantic Gap in Image and Video Analysis: An Introduction
  • Low-Level Feature Detectors and Descriptors for Smart Image and Video Analysis: A Comparative Study
  • Scale-insensitive MSER Features: A Promising Tool for Meaningful Segmentation of Images
  • Active Partitions in Localization of Semantically Important Image Structures
  • Model-based 3D Object recognition in RGB-D Images
  • Ontology-Based Structured Video Annotation for Content-Based Video Retrieval via Spatiotemporal Reasoning
  • Deep Learning - a New Era in Bridging the Semantic Gap.

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