Very Deep Convolutional Networks for Large-Scale Image Recognition
Citations
264 citations
263 citations
Cites methods from "Very Deep Convolutional Networks fo..."
...We could see that our DenseNet outperformed LeNet and VGGNet....
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...As for the classification, Table 10 shows that our proposed DenseNet model performs better than the other popular deep networks such as the LeNet and VGGNet....
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...The first experiment was to test the classification performances of DenseNet when compared to other deep networks such as the popular LeNet (L ecun et al., 1998) and VGGNet (Simonyan and Zisserman, 2014)....
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...Recently, deep learning networks, including convolutional neural networks (CNNs), have been widely used in image classification and computer vision (Chen et al., 2016; Liu et al., 2014, 2017, 2018b; Ng et al., 2015; Simonyan and Zisserman, 2014; Wang et al., 2017)....
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...The LeNet network consists of 2 convolutional layers followed by 2 fully connected layers, while VGGNet consists of 13 convolutional layers and 3 fully connected layers....
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263 citations
263 citations
Cites background from "Very Deep Convolutional Networks fo..."
...Although several networks architectures were analysed in [27], [28], we have found only one study on “very deep CNN” [40], in which the number of convolutional layers was varied systematically (8-16) while keeping kernel sizes fixed....
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263 citations
Cites methods from "Very Deep Convolutional Networks fo..."
...We employ AlexNet [16] and VGG16 [34] pre-trained on ImageNet....
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References
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