Adaptive Blending Units: Trainable Activation Functions for Deep Neural Networks

DC ElementWertSprache
dc.contributor.authorSütfeld, Leon René
dc.contributor.authorBrieger, Flemming
dc.contributor.authorFinger, Holger
dc.contributor.authorFüllhase, Sonja
dc.contributor.authorPipa, Gordon
dc.date.accessioned2022-04-19T14:07:38Z-
dc.date.available2022-04-19T14:07:38Z-
dc.date.issued2020
dc.identifier.issn2194-5365
dc.identifier.urihttps://osnascholar.ub.uni-osnabrueck.de/handle/unios/55001-
dc.publisherSpringer, Cham
dc.relation.ispartofAdvances in intelligent systems and computing
dc.subjectComputer science
dc.subjectDeep learning
dc.subjectDeep neural networks
dc.subjectRecurrent neural network
dc.subjectActivation function
dc.subjectConvolutional neural network
dc.subjectTime delay neural network
dc.subjectPattern recognition (psychology)
dc.subjectArtificial neural network
dc.subjectArtificial intelligence
dc.titleAdaptive Blending Units: Trainable Activation Functions for Deep Neural Networks
dc.typebook part
dc.identifier.doihttps://doi.org/10.1007/978-3-030-52243-8_4
dc.description.startpage37
dc.description.endpage50
dc.identifier.externalhttps://openalex.org/W3042896572
dcterms.oaStatustrue
local.import.sourcefileopenalex_uos_20220409.ris
crisitem.author.deptInstitut für Kognitionswissenschaft-
crisitem.author.deptidinstitute28-
crisitem.author.orcid0000-0002-3416-2652-
crisitem.author.parentorgFB 08 - Humanwissenschaften-
crisitem.author.grandparentorgUniversität Osnabrück-
crisitem.author.netidPiGo340-
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