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Deep learning: basics and convolutional neural networks (CNN)

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اقرأ أكثر حفظ في قائمتي
  • معلومة اضافية
    • Contributors:
      CentraleSupélec; Algorithms, models and methods for images and signals of the human brain (ARAMIS); Sorbonne Université (SU)-Inria de Paris; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM); Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière AP-HP; Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière AP-HP; Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS); Laboratoire d'Informatique Gaspard-Monge (LIGM); École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Université Gustave Eiffel; Olivier Colliot; ANR-19-P3IA-0001,PRAIRIE,PaRis Artificial Intelligence Research InstitutE(2019)
    • بيانات النشر:
      HAL CCSD
      Springer
    • الموضوع:
      2023
    • Collection:
      Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe)
    • نبذة مختصرة :
      International audience ; Deep learning belongs to the broader family of machine learning methods and currently provides state-of-the-art performance in a variety of fields, including medical applications. Deep learning architectures can be categorized into different groups depending on their components. However, most of them share similar modules and mathematical formulations. In this chapter, the basic concepts of deep learning will be presented to provide a better understanding of these powerful and broadly used algorithms. The analysis is structured around the main components of deep learning architectures, focusing on convolutional neural networks and autoencoders.
    • Relation:
      hal-03957224; https://hal.science/hal-03957224; https://hal.science/hal-03957224/document; https://hal.science/hal-03957224/file/Chapter%203%20-%20Final.pdf
    • Rights:
      http://creativecommons.org/licenses/by/ ; info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.93130817