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GENERATING SYNTHETIC MODELS OR VIRTUAL OBJECTS FOR TRAINING A DEEP LEARNING NETWORK

机译:训练深层学习网络的综合模型或虚拟对象

摘要

In some implementations, a training platform may receive data for generating synthetic models of a body part, such as a hand. The data may include information relating to a plurality of potential poses of the hand. The training platform may generate a set of synthetic models of the hand based on the information, where each synthetic model, in the set of synthetic models, representing a respective pose of the plurality of potential poses. The training platform may derive an additional set of synthetic models based on the set of synthetic models by performing one or more processing operations with respect to at least one synthetic model in the set of synthetic models, and causing the set of synthetic models and the additional set of synthetic models to be provided to a deep learning network to train the deep learning network to perform image segmentation, object recognition, or motion recognition.
机译:在一些实施方式中,训练平台可以接收用于生成诸如手的身体部位的合成模型的数据。该数据可以包括与手的多个潜在姿势有关的信息。训练平台可以基于该信息来生成手的一组合成模型,其中该组合成模型中的每个合成模型代表多个潜在姿势中的相应姿势。训练平台可以通过针对一组合成模型中的至少一个合成模型执行一个或多个处理操作,并基于该组合成模型来导出另一组合成模型,并导致该组合成模型和其他一组合成模型将提供给深度学习网络,以训练深度学习网络执行图像分割,对象识别或运动识别。

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