| 1. Identity statement | ||||
| Reference Type | Conference Paper (Conference Proceedings) | |||
| Site | sibgrapi.sid.inpe.br | |||
| Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH | |||
| Identifier | 8JMKD3MGPEW34M/45EKAQE | |||
| Repository | sid.inpe.br/sibgrapi/2021/09.17.01.14 | |||
| Last Update | 2021:09.17.01.14.32 (UTC) administrator | |||
| Metadata Repository | sid.inpe.br/sibgrapi/2021/09.17.01.14.32 | |||
| Metadata Last Update | 2022:09.10.00.16.17 (UTC) administrator | |||
| Citation Key | YasudaCappMartGrip:2021:AuViIn | |||
| Title | Automated Visual Inspection of Aircraft Exterior Using Deep Learning  | |||
| Format | On-line | |||
| Year | 2021 | |||
| Access Date | 2024, Apr. 20 | |||
| Number of Files | 1 | |||
| Size | 236 KiB | |||
| 2. Context | ||||
| Author | 1 Yasuda, Yuri Del Vigna 2 Cappabianco, Fabio Augusto Menocci 3 Martins, Luiz Eduardo Galvão 4 Gripp, Jorge Augusto de Bonfim | |||
| Affiliation | 1 Universidade Federal de São Paulo 2 Universidade Federal de São Paulo 3 Universidade Federal de São Paulo 4 Autaza Technology | |||
| Editor | Paiva, 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 Address | yuri.yasuda@unifesp.br | |||
| Conference Name | Conference on Graphics, Patterns and Images, 34 (SIBGRAPI) | |||
| Conference Location | Gramado, RS, Brazil (virtual) | |||
| Date | 18-22 Oct. 2021 | |||
| Publisher | Sociedade Brasileira de Computação | |||
| Publisher City | Porto Alegre | |||
| Book Title | Proceedings | |||
| Tertiary Type | Work in Progress | |||
| History (UTC) | 2021-09-17 01:14:32 :: yuri.yasuda@unifesp.br -> administrator :: 2022-09-10 00:16:17 :: administrator -> :: 2021 | |||
| 3. Content and structure | ||||
| Is the master or a copy? | is the master | |||
| Content Stage | completed | |||
| Transferable | 1 | |||
| Keywords | Aircraft visual inspection Systematic literature review Defect detection Deep learning | |||
| Abstract | Aircraft visual inspections, or General Visual Inspections (GVIs), aim at finding damages or anomalies on the exterior and interior surfaces of the aircraft, which might compromise its operation, structure, or safety when flying. Visual inspection is part of the activities of aircraft Maintenance, Repair and Overhaul (MRO). Specialists perform quality inspections to identify problems and determine the type and importance that they will report. This process is time-consuming, subjective, and varies according to each individual. The time that an aircraft stays grounded without flight clearance means financial losses. The main goal of this work is to advance the state-of-the-art of defect detection on aircraft exterior with deep learning and computer vision. We investigate improvements to the accuracy of dent detection. Besides, we investigate new classes of identified defects, such as scratches. We also plan to demonstrate that it is possible to develop a complete system to automate the visual inspection of aircraft exterior using images of the aircraft acquired by drones. We will use deep neural networks for the detection and segmentation of defective regions. This system will aid in the elimination of subjectivity caused by human errors and shorten the time required to inspect an aircraft, bringing benefits to its safety, maintenance, and operation. | |||
| Arrangement | urlib.net > SDLA > Fonds > SIBGRAPI 2021 > Automated Visual Inspection... | |||
| doc Directory Content | access | |||
| source Directory Content | there are no files | |||
| agreement Directory Content |
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| 4. Conditions of access and use | ||||
| data URL | http://urlib.net/ibi/8JMKD3MGPEW34M/45EKAQE | |||
| zipped data URL | http://urlib.net/zip/8JMKD3MGPEW34M/45EKAQE | |||
| Language | en | |||
| Target File | Aircraft_Visual_Inspection__Work_In_Progress.pdf | |||
| User Group | yuri.yasuda@unifesp.br | |||
| Visibility | shown | |||
| 5. Allied materials | ||||
| Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 | |||
| Next Higher Units | 8JMKD3MGPEW34M/45PQ3RS | |||
| Citing Item List | sid.inpe.br/sibgrapi/2021/11.12.11.46 3 sid.inpe.br/banon/2001/03.30.15.38.24 1 | |||
| Host Collection | sid.inpe.br/banon/2001/03.30.15.38 | |||
| 6. Notes | ||||
| Empty Fields | archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi 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 versiontype volume | |||