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Classification and Visualisation of Normal and Abnormal Radiographs; A Comparison between Eleven Convolutional Neural Network Architectures

This paper investigates the classification of radiographic images with eleven convolutional neural network (CNN) architectures (<i>GoogleNet, VGG-19, AlexNet, SqueezeNet, ResNet-18, Inception-v3, ResNet-50, VGG-16, ResNet-101, DenseNet-201 and Inception-ResNet-v2</i>). The CNNs were used to classify...

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Principais autores: Ananda Ananda, Kwun Ho Ngan, Cefa Karabağ, Aram Ter-Sarkisov, Eduardo Alonso, Constantino Carlos Reyes-Aldasoro
Formato: Artigo
Idioma:Inglês
Publicado em: MDPI AG 2021-08-01
coleção:Sensors
Assuntos:
wrist fractures
radiographic images
classification
convolutional neural networks
class activation mapping
Acesso em linha:https://www.mdpi.com/1424-8220/21/16/5381
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