Análise Comparativa de Redes Neurais Convolucionais no Reconhecimento de Cenas
Victor Souza, Luan Oliveira da Silva, Adam Santos, Leandro Araújo · Anais do XI Computer on the Beach - COTB '20 · 2020
This paper aims to compare the convolutional neural networks(CNNs): ResNet50, InceptionV3, and InceptionResNetV2 tested withand without pre-trained weights on the ImageNet database in orderto solve the scene recognition problem. The results showed that thepre-trained ResNet50 achieved the best performance with an averageaccuracy of 99.82% in training and 85.53% in the test, while theworst 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 comparisonbetween the CNNs widely applied in the literature, that is,to enable a better selection of the algorithms in the various scenerecognition applications.