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- 01HG07Y1H2FHPQAPK6NEG6G36A classification C1.
- 01HG07Y1H2FHPQAPK6NEG6G36A date "2023".
- 01HG07Y1H2FHPQAPK6NEG6G36A language "eng".
- 01HG07Y1H2FHPQAPK6NEG6G36A type conference.
- 01HG07Y1H2FHPQAPK6NEG6G36A hasPart 01HG083B2SXPTVWBTRM7VXXH88.pdf.
- 01HG07Y1H2FHPQAPK6NEG6G36A hasPart 01HQJQ9CV2H7PJEEM3RN06ZBFP.pdf.
- 01HG07Y1H2FHPQAPK6NEG6G36A subject "Technology and Engineering".
- 01HG07Y1H2FHPQAPK6NEG6G36A doi "10.1109/WHISPERS61460.2023.10431111".
- 01HG07Y1H2FHPQAPK6NEG6G36A isbn "9798350395570".
- 01HG07Y1H2FHPQAPK6NEG6G36A issn "2158-6276".
- 01HG07Y1H2FHPQAPK6NEG6G36A presentedAt urn:uuid:a8d90407-d5d8-48cf-ade7-0ede2cd07ee4.
- 01HG07Y1H2FHPQAPK6NEG6G36A abstract "High-voltage transmission towers require regular inspections to identify corrosion. Traditionally, these inspections are performed through climbing, involving skilled technicians. This method is both tedious and hazardous, often necessitating the shut-down of sections of the high-voltage grid. In this paper we propose a workflow that relies on drone-based hyperspectral imaging, which enables remote assessment without endangering the technician. Currently, drones are equipped with conventional RGB cameras. However, these cameras have limited spectral resolution and range, which compromises their ability to reliably detect corrosion and often leads to false alarms. Moreover, conventional RGB cameras are unsuitable for accurately assessing the severity of corroded areas. To address these challenges, this study proposes a solution that leverages hyperspectral imaging and a dedicated processing pipeline to robustly detect corrosion and classify it based on severity level. Experiments using drones equipped with imec's VIS-NIR hyperspectral payload demonstrated the effectiveness of our developed solution.".
- 01HG07Y1H2FHPQAPK6NEG6G36A author 0F70FE1E-F0EE-11E1-A9DE-61C894A0A6B4.
- 01HG07Y1H2FHPQAPK6NEG6G36A author 63605158-5F1A-11E5-BC83-33E2B4D1D7B1.
- 01HG07Y1H2FHPQAPK6NEG6G36A author F6C3B776-F0ED-11E1-A9DE-61C894A0A6B4.
- 01HG07Y1H2FHPQAPK6NEG6G36A author F9970610-F0ED-11E1-A9DE-61C894A0A6B4.
- 01HG07Y1H2FHPQAPK6NEG6G36A author urn:uuid:0ece24c7-e82c-4f82-a261-5902f2b45508.
- 01HG07Y1H2FHPQAPK6NEG6G36A author urn:uuid:18fd4b2e-4709-4e71-92e0-9e5142ed498b.
- 01HG07Y1H2FHPQAPK6NEG6G36A author urn:uuid:502806fa-ef40-4aed-81f9-70232868c592.
- 01HG07Y1H2FHPQAPK6NEG6G36A author urn:uuid:5eb8c571-aca5-42fa-b150-c0cbda481609.
- 01HG07Y1H2FHPQAPK6NEG6G36A author urn:uuid:65795198-5fe5-4dd2-b624-114c40640f3f.
- 01HG07Y1H2FHPQAPK6NEG6G36A author urn:uuid:af2c71bf-38a9-4f11-9711-e24671bbc94b.
- 01HG07Y1H2FHPQAPK6NEG6G36A author urn:uuid:bd64f96a-a2a5-46d3-9ed8-9244acdf00aa.
- 01HG07Y1H2FHPQAPK6NEG6G36A author urn:uuid:cbd4fc93-0172-40b2-94e7-c86a623c21cb.
- 01HG07Y1H2FHPQAPK6NEG6G36A dateCreated "2023-11-24T08:42:53Z".
- 01HG07Y1H2FHPQAPK6NEG6G36A dateModified "2024-10-29T18:34:00Z".
- 01HG07Y1H2FHPQAPK6NEG6G36A name "Drone-based corrosion detection on high-voltage transmission towers using hyperspectral imaging".
- 01HG07Y1H2FHPQAPK6NEG6G36A pagination urn:uuid:c920c4fb-53ca-4549-951d-409d08a8fc46.
- 01HG07Y1H2FHPQAPK6NEG6G36A publisher urn:uuid:f2e46218-54b4-43f1-b1d5-166bc149c12f.
- 01HG07Y1H2FHPQAPK6NEG6G36A sameAs LU-01HG07Y1H2FHPQAPK6NEG6G36A.
- 01HG07Y1H2FHPQAPK6NEG6G36A sourceOrganization urn:uuid:1cb721d8-5b08-4c1b-9349-6caab94d6d4b.
- 01HG07Y1H2FHPQAPK6NEG6G36A sourceOrganization urn:uuid:dc5cbfa0-c929-4767-bef7-bb4983bf1774.
- 01HG07Y1H2FHPQAPK6NEG6G36A type C1.