Projecten per jaar
Samenvatting
Seabed characterisation consists in the study of the physical and biological properties of the bottom of the oceans. It is effectively achieved with sonar, a remote sensing method that captures acoustic backscatter of the seabed. Classical Machine Learning (ML) and Deep Learning (DL) research have failed to successfully address the automatic mapping of the seabed from noisy sonar data. This work introduces the Deep Supervised Semantic Segmentation model for Seabed Characterisation (D4SC), a novel U-Net-like model tailored to such data and low-label regime, and proposes a new end-to-end processing pipeline for seabed semantic segmentation. That dual contribution achieves state-of-the-art results on a high resolution Synthetic Aperture Sonar (SAS) survey dataset.
Originele taal-2 | Engels |
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Titel | IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings |
Uitgeverij | Institute of Electrical and Electronics Engineers Inc. |
Pagina's | 6932-6935 |
Aantal pagina's | 4 |
ISBN van elektronische versie | 9798350320107 |
DOI's | |
Status | Gepubliceerd - 2023 |
Evenement | 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 - Pasadena, Verenigde Staten van Amerika Duur: 16 jul. 2023 → 21 jul. 2023 https://2023.ieeeigarss.org/ |
Publicatie series
Naam | International Geoscience and Remote Sensing Symposium (IGARSS) |
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Volume | 2023-July |
Congres
Congres | 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 |
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Verkorte titel | IGARSS 2023 |
Land/Regio | Verenigde Staten van Amerika |
Stad | Pasadena |
Periode | 16/07/23 → 21/07/23 |
Internet adres |
Vingerafdruk
Duik in de onderzoeksthema's van 'D4SC: Deep Supervised Semantic Segmentation for Seabed Characterisation in Low-Label Regime'. Samen vormen ze een unieke vingerafdruk.Projecten
- 1 Actief
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DAP/21-11: Automatic, small-scale sea-floor characterization from high-resolution sonar data
Lopera Tellez, O. (Promotor), Neyt, X. (Promotor) & Arhant, Y. (Onderzoeker)
1/09/21 → 31/08/25
Project: Onderzoek