Isbn: 9783330353060 - hierarchical approach for object detection using shape descriptors (7 risultati)

Perfeziona la tua ricerca

  • Libri (7)

  • Nuovo (7)

a

Fascia di prezzo personalizzata (EUR)

a

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2019

    3330353066 / 9783330353060

    • Brossura

    Da: Books Puddle, Woodside, NY, U.S.A.Books Puddle

    Venditore con 4 stelle
    Contatta il venditore

    Condizione: Nuovo

    EUR 68,56

    EUR 3,56 spedizione 
    Spedito in U.S.A.

    Quantità: 4 disponibili

    Condizione: New.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing Mai 2019, 2019

    3330353066 / 9783330353060

    • Brossura
    • Print on Demand

    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

    Venditore con 5 stelle
    Contatta il venditore

    Condizione: Nuovo

    EUR 39,90

    EUR 23,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 2 disponibili

    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Automatic object recognition is a fundamental problem in the fields of computer vision and machine learning, that has received a lot of research attention lately. While there are different methods, that build upon various low level features to construct object models, this work explores and implements the use of closed-contours as formidable object features. A hierarchical technique is employed to extract the contours, exploiting the inherent spatial relationships between the parent and child contours of an object. Fourier Descriptors are used to effectively and invariantly describe the extracted contours. A simple hierarchical, shape label and spatial descriptor matching method is implemented, to determine the nearest object-model. Multi-threaded architecture and GPU efficient image-processing functions are adopted making the technique efficient for use in real world applications. The technique is successfully tested on common traffic signs in real world images, with overall good performance and robustness being obtained as an end result. 56 pp. Englisch. …

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2019

    3330353066 / 9783330353060

    • Brossura
    • Print on Demand

    Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

    Venditore con 4 stelle
    Contatta il venditore

    Condizione: Nuovo

    EUR 68,70

    EUR 7,67 spedizione 
    Spedito da Regno Unito a U.S.A.

    Quantità: 4 disponibili

    Condizione: New. Print on Demand.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2019

    3330353066 / 9783330353060

    • Brossura
    • Print on Demand

    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

    Venditore con 5 stelle
    Contatta il venditore

    Condizione: Nuovo

    EUR 40,38

    EUR 35,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 1 disponibile

    Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Automatic object recognition is a fundamental problem in the fields of computer vision and machine learning, that has received a lot of research attention lately. While there are different methods, that build upon various low level features to construct object models, this work explores and implements the use of closed-contours as formidable object features. A hierarchical technique is employed to extract the contours, exploiting the inherent spatial relationships between the parent and child contours of an object. Fourier Descriptors are used to effectively and invariantly describe the extracted contours. A simple hierarchical, shape label and spatial descriptor matching method is implemented, to determine the nearest object-model. Multi-threaded architecture and GPU efficient image-processing functions are adopted making the technique efficient for use in real world applications. The technique is successfully tested on common traffic signs in real world images, with overall good performance and robustness being obtained as an end result.…

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2019

    3330353066 / 9783330353060

    • Brossura
    • Print on Demand

    Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

    Venditore con 4 stelle
    Contatta il venditore

    Condizione: Nuovo

    EUR 69,14

    EUR 9,95 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 4 disponibili

    Condizione: New. PRINT ON DEMAND.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2019

    3330353066 / 9783330353060

    • Brossura
    • Print on Demand

    Da: moluna, Greven, Germaniamoluna

    Venditore con 5 stelle
    Contatta il venditore

    Condizione: Nuovo

    EUR 34,25

    EUR 48,99 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: Più di 20 disponibili

    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Arshad Bassam SyedBassam Syed Arshad - Graduate College of The University of Texas, Rio Grande Valley. Degree of Master of Science.Automatic object recognition is a fundamental problem in the fields of computer vision and machine.…

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing Mai 2019, 2019

    3330353066 / 9783330353060

    • Brossura
    • Print on Demand

    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

    Venditore con 5 stelle
    Contatta il venditore

    Condizione: Nuovo

    EUR 39,90

    EUR 60,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 1 disponibile

    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Automatic object recognition is a fundamental problem in the fields of computer vision and machine learning, that has received a lot of research attention lately. While there are different methods, that build upon various low level features to construct object models, this work explores and implements the use of closed-contours as formidable object features. A hierarchical technique is employed to extract the contours, exploiting the inherent spatial relationships between the parent and child contours of an object. Fourier Descriptors are used to effectively and invariantly describe the extracted contours. A simple hierarchical, shape label and spatial descriptor matching method is implemented, to determine the nearest object-model. Multi-threaded architecture and GPU efficient image-processing functions are adopted making the technique efficient for use in real world applications. The technique is successfully tested on common traffic signs in real world images, with overall good performance and robustness being obtained as an end result.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.…