MUTE: Inter-class Ambiguity Driven Multi-hot Target Encoding for Deep Neural Network Design

摘要

Target encoding is an effective technique to boost performance of classical and deep neural networks based classification models. However, the existing target encoding approaches require significant increase in the learning capacity, thus demand higher co