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Orientador(es)
Resumo(s)
Catastrophic forgetting arises when a neural network is not
capable of preserving the past learned task when learning a new task.
There are already some methods proposed to mitigate this problem in
arti cial neural networks. In this paper we propose to improve upon
our previous state-of-the-art method, SeNA-CNN, such as to enable the
automatic recognition in test time of the task to be solved and we experimentally
show that it has excellent results. The experiments show
the learning of up to 4 di erent tasks with a single network, without
forgetting how to solve previous learned tasks.
Descrição
Palavras-chave
Supervised Learning Lifelong learning Catastrophic Forgetting Convolutional Neural Networks