Neural networks for intelligent multimedia processing

Sun Yuan Kung, Jenq Neng Hwang

Research output: Contribution to journalArticle

45 Scopus citations

Abstract

This paper reviews key attributes of neural processing essential to intelligent multimedia processing (IMP). The objective is to show why neural nertvorks (NN's) are a core technology for the following multimedia functionalities: I) efficient representations for audio/visual information, 2) detection and classification techniques, 3) fusion of inultimodal signals, and 4) multimodal conversion and synchronization. It also demonstrates how the adaptive NN technology presents a unified solution to a broad spectrum of multimedia applications. As substantiating evidence, representative examples where NN's are successfully applied to IMP applications are highlighted. The examples cover a broad range, including image visualization, tracking of moving objects, image/video segmentation, texture classification, face-object detection/recognition, audio classification, inultimodal recognition, and inultimodal lip reading.

Original languageEnglish (US)
Pages (from-to)1244-1271
Number of pages28
JournalProceedings of the IEEE
Volume86
Issue number6
DOIs
StatePublished - Jan 1 1998

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Keywords

  • ACON/OCON nehvorks
  • Access-control security
  • Active contour model
  • Adaptive expectation-maximization
  • Audio classification
  • Audio-to-visual conversion
  • Audio/visual fusion
  • Decision-based neural network
  • Face recognition

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