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Label noise is not uncommon in machine learning applications nowadays and imposes great challenges for many existing classifiers. In this paper we propose a new type of auto-encoder coined label-denoising auto-encoder to learn a representation for robust classification under this situation. For this purpose, we include both the feature and the (noisy) label of a data point in the input layer of the...
Face detection has been a very active research topic in recent years. However, when applied to uncontrolled environments, some systems exhibit poor generalization ability. Even though few of existing methods can achieve promising results in some challenging situations, they usually have the requirement of high computational cost. This will definitely limit the use of those methods in some mobile platforms...
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