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SeNA-CNN: Overcoming Catastrophic Forgetting in Convolutional Neural Networks by Selective Network Augmentation

dc.contributor.authorZacarias, Abel
dc.contributor.authorAlexandre, Luís
dc.date.accessioned2020-01-09T10:18:43Z
dc.date.available2020-01-09T10:18:43Z
dc.date.issued2018
dc.description.abstractLifelong learning aims to develop machine learning systems that can learn new tasks while preserving the performance on previous learned tasks. In this paper we present a method to overcome catastrophic forgetting on convolutional neural networks, that learns new tasks and preserves the performance on old tasks without accessing the data of the original model, by selective network augmentation. The experiment results showed that SeNA-CNN, in some scenarios, outperforms the state-of-art Learning without Forgetting algorithm. Results also showed that in some situations it is better to use SeNA-CNN instead of training a neural network using isolated learning.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1007/978-3-319-99978-4_8pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.6/8143
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectLifelong Learningpt_PT
dc.subjectCatastrophic Forgettingpt_PT
dc.subjectConvolutional Neural Networkspt_PT
dc.subjectSupervised Learningpt_PT
dc.titleSeNA-CNN: Overcoming Catastrophic Forgetting in Convolutional Neural Networks by Selective Network Augmentationpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.endPage112pt_PT
oaire.citation.startPage102pt_PT
oaire.citation.volume11081pt_PT
person.familyNameZacarias
person.familyNameAlexandre
person.givenNameAbel
person.givenNameLuís
person.identifier.ciencia-id7612-6C59-2F02
person.identifier.ciencia-id2014-0F06-A3E3
person.identifier.orcid0000-0002-0226-9682
person.identifier.orcid0000-0002-5133-5025
person.identifier.ridE-8770-2013
person.identifier.scopus-author-id8847713100
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication9f46b558-e59e-4c92-95ac-7f3f06b0ed16
relation.isAuthorOfPublication131ec6eb-b61a-4f27-953f-12e948a43a96
relation.isAuthorOfPublication.latestForDiscovery131ec6eb-b61a-4f27-953f-12e948a43a96

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