Close
Metadata

1. Identity statement
Reference TypeOther (Misc)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPEW34M/45CGCRL
Repositorysid.inpe.br/sibgrapi/2021/09.04.02.00
Last Update2021:09.04.02.00.40 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2021/09.04.02.00.40
Metadata Last Update2022:05.15.22.30.28 (UTC) administrator
Citation KeySousaFernVasc:2021:NoSeNe
TitleConformalLayers: A non-linear sequential neural network with associative layers
Short TitleSupplemerntary material
FormatOn-line
Year2021
Date18-22 Oct. 2021
Access Date2024, May 19
Number of Files1
Size490 KiB
2. Context
Author1 Sousa, Eduardo Vera
2 Fernandes, Leandro A. F.
3 Vasconcelos, Cristina Nader
Affiliation1 Universidade Federal Fluminense
2 Universidade Federal Fluminense
3 Universidade Federal Fluminense
e-Mail Addresseduardovera@ic.uff.br
History (UTC)2021-09-04 02:00:40 :: eduardovera@ic.uff.br -> administrator ::
2022-05-15 22:30:28 :: administrator -> eduardovera@ic.uff.br :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsconvolutional neural network
non-linear activation
associativity
AbstractConvolutional Neural Networks (CNNs) have been widely applied. But as the CNNs grow, the number of arithmetic operations and memory footprint also increases. Furthermore, typical non-linear activation functions do not allow associativity of the operations encoded by consecutive layers, preventing the simplification of intermediate steps by combining them. We present a new activation function that allows associativity between sequential layers of CNNs. Even though our activation function is non-linear, it can be represented by a sequence of linear operations in the conformal model for Euclidean geometry. In this domain, operations like, but not limited to, convolution, average pooling, and dropout remain linear. We take advantage of associativity to combine all the "conformal layers" and make the cost of inference constant regardless of the depth of the network.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2021 > ConformalLayers: A non-linear... > Supplemerntary material
Arrangement 2urlib.net > SDLA > Fonds > Full Index > ConformalLayers: A non-linear... > Supplemerntary material
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 03/09/2021 23:00 2.0 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/45CGCRL
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/45CGCRL
Languageen
Target FileSupplementaryMaterial.pdf
User Groupeduardovera@ic.uff.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/45CGCM8
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber city contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi edition electronicmailaddress group holdercode howpublished isbn issn label lineage mark nextedition notes number numberofpages orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype session sponsor subject tertiarymark tertiarytype type url versiontype
7. Description control
e-Mail (login)eduardovera@ic.uff.br
update 


Close