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In this book, an overview of DL is presented that adopts various perspectives such as state-of-the-arts deep learning techniques, Deep learning approaches, applications. Additionally, the potential problems on deep learning technology. This research presents convolutional neural networks (CNNs) which the most utilized DL network type. A survey of the CNN deep learning architectures that are frequently encountered in the literature, along with their strengths and limitations and describes the development of CNNs architectures together with their main features, e.g., AlexNet, VGG, ResNet, DenseNet, GoogLeNet, Inception: ResNet nd Inception V3/ V4, SegNet, U Net, Point CNN and MASK R-CNN .A detailed study on application of Convolutional Neural Network on the remote sensing to extract features is also explained. Challenges that met CNN were discussed.
Über den Autor / die Autorin
Dr. Lamyaa Gamal Eldeen Taha Professeur en topographie et photogrammétrie Chef de la division Aviation et photographie aérienne - Autorité nationale pour la télédétection et les sciences spatiales Dr. Rania E. Ibrahim Chef du département des publications scientifiques - Autorité nationale pour la télédétection et les sciences spatiales Ing.Asmaa A.Mandouh NARSS.
