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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/45CUKQ8
Repositorysid.inpe.br/sibgrapi/2021/09.06.21.01
Last Update2021:10.08.22.36.53 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2021/09.06.21.01.28
Metadata Last Update2022:06.14.00.00.31 (UTC) administrator
DOI10.1109/SIBGRAPI54419.2021.00044
Citation KeyJerripothulaAnsaNijh:2021:ViSoTr
TitleA Vision-based Solution for Track Misalignment Detection
FormatOn-line
Year2021
Access Date2024, July 22
Number of Files1
Size1619 KiB
2. Context
Author1 Jerripothula, Koteswar Rao
2 Ansari, Sharik Ali
3 Nijhawan, Rahul
Affiliation1 Indraprastha Institute of Information Technology Delhi (IIIT-Delhi) 
2 College of Engineering Roorkee (COER) 
3 University of Petroleum and Energy Studies (UPES)
EditorPaiva, Afonso
Menotti, David
Baranoski, Gladimir V. G.
Proença, Hugo Pedro
Junior, Antonio Lopes Apolinario
Papa, João Paulo
Pagliosa, Paulo
dos Santos, Thiago Oliveira
e Sá, Asla Medeiros
da Silveira, Thiago Lopes Trugillo
Brazil, Emilio Vital
Ponti, Moacir A.
Fernandes, Leandro A. F.
Avila, Sandra
e-Mail Addresskoteswar@iiitd.ac.in
Conference NameConference on Graphics, Patterns and Images, 34 (SIBGRAPI)
Conference LocationGramado, RS, Brazil (virtual)
Date18-22 Oct. 2021
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2021-10-08 22:36:54 :: koteswar@iiitd.ac.in -> administrator :: 2021
2022-03-02 00:54:16 :: administrator -> menottid@gmail.com :: 2021
2022-03-02 13:26:34 :: menottid@gmail.com -> administrator :: 2021
2022-06-14 00:00:31 :: administrator -> :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsrailway
transfer learning
VGG
Inception
AbstractDerailment is one of the most frequent ways railway accidents happen. Track defects such as buckling and hogging that cause misalignment of tracks can easily lead to derailments. While railway tracks get laterally misaligned due to buckling, vertical misalignments can result from hogging. Such misalignments are visibly recognizable, and we can even automate recognition using data-driven models. This paper discusses how we build such data-driven models. There are no public datasets available to build such models; therefore, we introduce TMD (Track Misalignment Detection) dataset. It consists of misaligned and normal track images. The problem we try to solve here is essentially a binary image classification problem, which we solve by exploring the feature extraction approach to transfer learning (TL). In this approach, we employ a pre-trained network to extract rich features, which are then supplied with annotations to a learning algorithm for building a candidate TL model. Several pre-trained networks and learning algorithms exist, resulting in multiple candidate TL models; therefore, it becomes essential to identify effective ones. We propose an evaluation criterion to decide which are effective ones using our proposed bias-variance analysis. Our experiments demonstrate that the candidate TL models selected based on our proposed evaluation criterion perform better than other candidate TL models while testing.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2021 > A Vision-based Solution...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > A Vision-based Solution...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 06/09/2021 18:01 1.3 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/45CUKQ8
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/45CUKQ8
Languageen
Target FileSIBGRAPI_Railway (3).pdf
User Groupkoteswar@iiitd.ac.in
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/45PQ3RS
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2021/11.12.11.46 25
sid.inpe.br/banon/2001/03.30.15.38.24 3
sid.inpe.br/sibgrapi/2022/06.10.21.49 2
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


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