The article considers the possibilities of using the deep learning convolutional neural network ResNet in computer vision and image classification problems. The interpretation of the ResNet network and the datasets used for its training are presented, as well as a method for training a deep convolutional neural network with stochastic depth, which allows significantly reducing errors in the test sample.

中文翻译：

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计算机视觉和图像分类问题中深度学习的卷积神经网络

本文考虑了在计算机视觉和图像分类问题中使用深度学习卷积神经网络 ResNet 的可能性。介绍了 ResNet 网络和用于其训练的数据集的解释，以及一种用于训练具有随机深度的深度卷积神经网络的方法，该方法可以显着减少测试样本中的错误。