• Resumo

    Análise Comparativa de Redes Neurais Convolucionais no Reconhecimento de Cenas

    Data de publicação: 04/09/2020

    ABSTRACT
    This paper aims to compare the convolutional neural networks
    (CNNs): ResNet50, InceptionV3, and InceptionResNetV2 tested with
    and without pre-trained weights on the ImageNet database in order
    to solve the scene recognition problem. The results showed that the
    pre-trained ResNet50 achieved the best performance with an average
    accuracy of 99.82% in training and 85.53% in the test, while the
    worst result was attributed to the ResNet50 without pre-training,
    with 88.76% and 71.66% of average accuracy in training and testing,
    respectively. The main contribution of this work is the direct comparison
    between the CNNs widely applied in the literature, that is,
    to enable a better selection of the algorithms in the various scene
    recognition applications.

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