Development and experimental evaluation of a machine learning assisted lwir polarimetric imaging system for transport anomaly detection
| dc.contributor.author | Pařez, Jan | |
| dc.contributor.author | Kovář, Patrik | |
| dc.contributor.author | Tater, Adam | |
| dc.contributor.author | Ballada, Ondřej | |
| dc.contributor.author | Barta, Čestmír | |
| dc.contributor.editor | Rendl, Jan | |
| dc.date.accessioned | 2026-04-30T09:44:41Z | |
| dc.date.available | 2026-04-30T09:44:41Z | |
| dc.date.issued | 2026 | |
| dc.description.abstract-translated | This paper presents the development and experimental evaluation of an intelligent system using long-wave infrared (LWIR) polarimetric imaging combined with machine learning. By exploiting polarization-based contrast mechanisms, the approach improves detection of surface features that are difficult to identify with conventional methods. The work includes the design of an experimental setup and the creation of a representative LWIR polarimetric dataset. A modular framework integrating convolutional neural networks and image quality metrics enables automated scene interpretation. Results demonstrate enhanced detection of transport-related phenomena such as thin liquid films, surfaces, and hidden contamination, supporting future mobility and safety applications. | en |
| dc.description.sponsorship | TQ15000307 | en |
| dc.format | 5 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.identifier.isbn | 978-80-261-1352-2 | |
| dc.identifier.uri | http://hdl.handle.net/11025/67904 | |
| dc.language.iso | en | en |
| dc.publisher | University of West Bohemia in Pilsen | en |
| dc.rights | © University of West Bohemia in Pilsen | en |
| dc.rights.access | openAccess | en |
| dc.subject | LWIR polarimetrie | cs |
| dc.subject | strojové učení | cs |
| dc.subject | monitorování transportu | cs |
| dc.subject | detekce anomálií | cs |
| dc.subject.translated | LWIR polarimetry | en |
| dc.subject.translated | machine learning | en |
| dc.subject.translated | transport monitoring | en |
| dc.subject.translated | anomaly detection | en |
| dc.title | Development and experimental evaluation of a machine learning assisted lwir polarimetric imaging system for transport anomaly detection | en |
| dc.type | konferenční příspěvek | cs |
| dc.type | conferenceObject | en |
| dc.type.version | publishedVersion | en |
| local.files.count | 2 | * |
| local.files.size | 1440721 | * |
| local.has.files | yes | * |
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