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2018 3rd International Conference for Convergence in Technology (I2CT)
This research paper describes a simplistic architecture named as AANN: Absolute Artificial Neural Network, which can be used to create highly interpretable representations of the input data. These representations are generated by penalizing the learning of the network in such a way that those learned representations correspond to the respective labels present in the labelled dataset used for supervised training; thereby, simultaneously giving the network the ability to classify the input data.doi:10.1109/i2ct.2018.8529552 fatcat:csckvdk5djbppia65inil32kyi