!!Research output per year
!!Research output per year
Projektdetails
Goal of the project
The aim of this study is threefold:
i. To develop an autonomous methodology for the characterization of environmental parameters to be injected in real-time into the target recognition process.
ii. To assess the operational performance of the techniques developed for target detection and recognition under the mine countermeasures capability replacement (rMCM) project.
iii. To create a database or model for the construction of Additional Military Layers to enhance environmental awareness for mine-search.
i. To develop an autonomous methodology for the characterization of environmental parameters to be injected in real-time into the target recognition process.
ii. To assess the operational performance of the techniques developed for target detection and recognition under the mine countermeasures capability replacement (rMCM) project.
iii. To create a database or model for the construction of Additional Military Layers to enhance environmental awareness for mine-search.
Funding acknowledgement
The project DAP/21-11 is financed under the DFR call.
| Status | Abgeschlossen |
|---|---|
| Tatsächlicher Beginn/ -es Ende | 1/09/21 → 31/08/25 |
Projektbeteiligte
- Royal Military Academy (Leitung)
- CMRE-STO
- University of Ghent
- ECA ROBOTICS
- ENSTA Bretagne
RHID domain
- DAP
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Publikationen
- 2 Konferenzbeitrag
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A new Deep Learning Neural Network Architecture for Seafloor Characterisation
Arhant, Y., Neyt, X. & Pizurica, A., 2 Okt. 2023, Proceedings of the NATO Military Sensing Symposium 2023. NATO Science and Technology Organization, 4 S. 92Publikation: Beitrag in Buch/Bericht/Konferenzband › Konferenzbeitrag
Open AccessDatei53 Downloads (Pure) -
D4SC: Deep Supervised Semantic Segmentation for Seabed Characterisation in Low-Label Regime
Arhant, Y., Tellez, O. L., Neyt, X. & Pizurica, A., 2023, IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc., S. 6932-6935 4 S. (International Geoscience and Remote Sensing Symposium (IGARSS); Band 2023-July).Publikation: Beitrag in Buch/Bericht/Konferenzband › Konferenzbeitrag › Begutachtung
Open AccessDatei2 Zitate (Scopus)44 Downloads (Pure)
Aktivitäten
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A new Deep Learning Neural Network Architecture for Seafloor Characterisation
Arhant, Y. (Redner), Neyt, X. (Co-author) & Pizurica, A. (Co-author)
21 Apr. 2023Aktivität: Gespräch oder Vortrag › Vortrag
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Artificial Intelligence for Seafloor Identification
Arhant, Y. (Redner), Lopera Tellez, O. (Redner), Neyt, X. (Co-author) & Pizurica, A. (Co-author)
19 Juni 2024Aktivität: Gespräch oder Vortrag › Vortrag
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Artificial Intelligence for Defence Seminars
Arhant, Y. (Teilnehmer)
1 Juli 2022Aktivität: Teilnahme an oder Organisation einer Veranstaltung › Participation to a Seminar