首页> 外文OA文献 >Figure 4: Training and test classification accuracies across training epochs: (A) training and test Top-1 accuracy with the AresB-10, AresB-18 and AresB-34 models on the ImageNet dataset; (B) training and test Top-5 accuracy with the AresB-10, AresB-18, and AresB-34 models on the ImageNet dataset.

【2h】

Figure 4: Training and test classification accuracies across training epochs: (A) training and test Top-1 accuracy with the AresB-10, AresB-18 and AresB-34 models on the ImageNet dataset; (B) training and test Top-5 accuracy with the AresB-10, AresB-18, and AresB-34 models on the ImageNet dataset.

机译：图4：培训和测试分类跨训练时期的准确性：（a）在想象网数据集上与ARESB-10，ARESB-18和ARESB-34模型进行培训和测试前1个精度; （b）培训和测试ARESB-10，ARESB-18和ImageNet DataSet上的Aresb-34模型的前5个精度。

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7. Figure 3: Training and test classification accuracies across training epochs: (A) training and test Top-1 accuracies with the AresB-10, AresB-18, and AresB-34 models on the CIFAR-10 dataset; (B) training and test Top-1 accuracies with the AresB-10, AresB-18, and AresB-34 models on the CIFAR-100 dataset. [O] . -1

机译：图3：培训和测试分类跨越时期的培训和测试分类准确性：（a）在CiFar-10数据集上培训和测试ARESB-10，ARESB-18和ARESB-34型号的前1个精度; （b）在CIFAR-100数据集上训练和测试ARESB-10，ARESB-18和ARESB-34型号的顶级精度。

Figure 4: Training and test classification accuracies across training epochs: (A) training and test Top-1 accuracy with the AresB-10, AresB-18 and AresB-34 models on the ImageNet dataset; (B) training and test Top-5 accuracy with the AresB-10, AresB-18, and AresB-34 models on the ImageNet dataset.

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