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SYSTEM AND METHOD FOR A CONVOLUTIONAL NEURAL NETWORK FOR MULTI-LABEL CLASSIFICATION WITH PARTIAL ANNOTATIONS
SYSTEM AND METHOD FOR A CONVOLUTIONAL NEURAL NETWORK FOR MULTI-LABEL CLASSIFICATION WITH PARTIAL ANNOTATIONS
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机译:带有部分注释的多标签分类的卷积神经网络的系统和方法
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摘要
Effectively training machine learning systems with incomplete/partial labels is a practical, technical problem that solutions described herein attempt to overcome. In particular, an approach to modify loss functions on a proportionality basis is noted in some embodiments. In other embodiments, a graph neural network is provided to help identify correlations/causations as between categories. In another set of embodiments, a prediction approach is described to, based on originally provided labels, predict labels for unlabelled training samples such that the proportion of labelled labels relative to all labels is increased.
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