Neural networks for intelligent multimedia processing

Sun Yuan Kung, Jenq Neng Hwang

Research output: Contribution to journalArticlepeer-review

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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