The AlexNet, LeNet-5 and VGG NET applied to CIFAR-10
The AlexNet, LeNet-5 and VGG NET applied to CIFAR-10
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AlexNet、LeNet-5 和 VGG NET 应用于 CIFAR-10
DOI：
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Xincheng Zhang
中科院分区：
文献类型：
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作者：
Xincheng Zhang
本文试图解决的问题是将AlexNet、LeNet-5和VGG Net应用到CIFAR-10数据库中，并说明这些结构的特点和性能。测试了多种训练策略，分别是AlexNet， LeNet5, VGG Net。这些神经网络算法由于在比赛中取得了很高的准确率而闻名。虽然它们不是为训练CIFAR-10而设计的，但这样一个优秀的模型是否能兼容不同的输入，值得探讨。因此，他们将在CIFAR-10上修改和测试性能。
The problem this work trying to solve is applying AlexNet, LeNet-5 and VGG Net to the CIFAR-10 database and tell the features and performance of these structures. Multiple strategies of training have been tested, they are respectively AlexNet, LeNet5, VGG Net. These neural network algorithms are famous since they have achieved high accuracy in competitions. Although they are not designed for training CIFAR-10, it is worth to exploit that whether such an excellent model compatible to different input. Therefore, they will modified and tested the performance on CIFAR-10.