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Identification of Partially Obscured Objects in two Dimensions by Matching of Noisy 'characteristic Curves, '

Bag om Identification of Partially Obscured Objects in two Dimensions by Matching of Noisy 'characteristic Curves, '

In this pioneering work, Schwartz and Sharir present a groundbreaking approach to the problem of object recognition in real-world situations. Drawing on insights from computational geometry, their algorithms are able to identify partially obscured objects with a high degree of accuracy. This book is essential reading for anyone interested in the science of perception and pattern recognition.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it.This work is in the "public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9781019461174
  • Indbinding:
  • Hardback
  • Sideantal:
  • 38
  • Udgivet:
  • 18. juli 2023
  • Størrelse:
  • 156x6x234 mm.
  • Vægt:
  • 236 g.
  • BLACK NOVEMBER
Leveringstid: 2-3 uger
Forventet levering: 11. december 2024

Beskrivelse af Identification of Partially Obscured Objects in two Dimensions by Matching of Noisy 'characteristic Curves, '

In this pioneering work, Schwartz and Sharir present a groundbreaking approach to the problem of object recognition in real-world situations. Drawing on insights from computational geometry, their algorithms are able to identify partially obscured objects with a high degree of accuracy. This book is essential reading for anyone interested in the science of perception and pattern recognition.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it.This work is in the "public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

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