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Machine Understanding

Machine Perception and Machine Perception MU

  • Zbigniew Les
  • Magdalena Les
Book

Part of the Studies in Computational Intelligence book series (SCI, volume 842)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Zbigniew Les, Magdalena Les
    Pages 1-8
  3. Zbigniew Les, Magdalena Les
    Pages 9-44
  4. Zbigniew Les, Magdalena Les
    Pages 45-62
  5. Zbigniew Les, Magdalena Les
    Pages 63-73
  6. Zbigniew Les, Magdalena Les
    Pages 75-95
  7. Zbigniew Les, Magdalena Les
    Pages 97-118
  8. Zbigniew Les, Magdalena Les
    Pages 119-140
  9. Zbigniew Les, Magdalena Les
    Pages 141-179
  10. Zbigniew Les, Magdalena Les
    Pages 181-215

About this book

Introduction

This unique book discusses machine understanding (MU). This new branch of classic machine perception research focuses on perception that leads to understanding and is based on the categories of sensory objects. In this approach the visual and non-visual knowledge, in the form of visual and non-visual concepts, is used in the complex reasoning process that leads to understanding. The book presents selected new concepts, such as perceptual transformations, within the machine understanding framework, and uses perceptual transformations to solve perceptual problems (visual intelligence tests) during understanding, where understanding is regarded as an ability to solve complex visual problems described in the authors’ previous books. Thanks to the uniqueness of the research topics covered, the book appeals to researchers from a wide range of disciplines, especially computer science, cognitive science and philosophy.


Keywords

Computational Intelligence Shape Understanding System Machine Understanding Complex Object Concept Knowledge Implementation

Authors and affiliations

  • Zbigniew Les
    • 1
  • Magdalena Les
    • 2
  1. 1.The St. Queen Jadwiga Research Institute of UnderstandingToorak, MelbourneAustralia
  2. 2.The St. Queen Jadwiga Research Institute of UnderstandingToorak, MelbourneAustralia

Bibliographic information