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Pattern Recognition Applications and Methods [electronic resource] : 9th International Conference, ICPRAM 2020, Valletta, Malta, February 22–24, 2020, Revised Selected Papers / edited by Maria De Marsico, Gabriella Sanniti di Baja, Ana Fred.

Medverkande: Materialtyp: TextSerie: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12594Utgivningsuppgift: Cham : Springer International Publishing : Imprint: Springer, 2020Utgåva: 1st ed. 2020Beskrivning: 1 online resource (XI, 139 p. 46 illus.). 41 illus. in colorInnehållstyp:
  • text
Medietyp:
  • computer
Bärartyp:
  • online resource
ISBN:
  • 9783030661250
Ämnen: Fler format: Printed edition:: Ingen titel; Printed edition:: Ingen titelDDK-klassifikation:
  • 006.4 23
Library of Congress (LC) klassifikationskod:
  • Q337.5
  • TK7882.P3
Onlineresurser:
Innehåll:
End to End Deep Neural Network Classifier Design for Universal Sign Recognition -- MaskADNet: MOTS based on ADNet -- Dimensionality Reduction and Attention Mechanisms for Extracting -- Efficient Radial Distortion Correction for Planar Motion -- Comparison of algorithms for Tree-top detection in Drone image mosaics of Japanese Mixed Forests -- Investigating Similarity Metrics for Convolutional Neural Networks in the Case of Unstructured Pruning -- Encoding of Indefinite Proximity Data: A Structure Preserving Perspective.
I: Springer Nature eBookSammanfattning: This book contains revised and extended versions of selected papers from the 9th International Conference on Pattern Recognition, ICPRAM 2020, held in Valletta, Malta, in February 2020. The 7 full papers presented were carefully reviewed and selected from 102 initial submissions. The papers describe applications of pattern recognition techniques to real-world problems, interdisciplinary research, experimental and theoretical studies yielding new insights that advance pattern recognition methods are especially encouraged.
Inga fysiska exemplar för denna post

End to End Deep Neural Network Classifier Design for Universal Sign Recognition -- MaskADNet: MOTS based on ADNet -- Dimensionality Reduction and Attention Mechanisms for Extracting -- Efficient Radial Distortion Correction for Planar Motion -- Comparison of algorithms for Tree-top detection in Drone image mosaics of Japanese Mixed Forests -- Investigating Similarity Metrics for Convolutional Neural Networks in the Case of Unstructured Pruning -- Encoding of Indefinite Proximity Data: A Structure Preserving Perspective.

This book contains revised and extended versions of selected papers from the 9th International Conference on Pattern Recognition, ICPRAM 2020, held in Valletta, Malta, in February 2020. The 7 full papers presented were carefully reviewed and selected from 102 initial submissions. The papers describe applications of pattern recognition techniques to real-world problems, interdisciplinary research, experimental and theoretical studies yielding new insights that advance pattern recognition methods are especially encouraged.

Print version record.

Licensed e-book