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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.

Análise Comparativa de Redes Neurais Convolucionais no Reconhecimento de Cenas