Mapping archeological signs from airborne lidar data using deep neural networks : Primary results

Summary, in English

– Complexity of large-scale Airborne LIDAR data: its processing, and interpretation emerges the necessity of automated analysis with novel techniques.

– Detection and documentation of archaeological ruins, hidden in the forests of the Swedish landscape.

• Författare: Melda Küçükdemirci; Giacomo Landeschi; Nicolo Dell'Unto; Mattias Ohlsson
• Avdelning/ar: Arkeologi; Digital Archaeology Laboratory DARK Lab; eSSENCE: The e-Science Collaboration; Computational Biology and Biological Physics - Has been reorganised
• Publiceringsår: 2021
• Språk: Engelska
• Sidor: 291-293
• Publikation/Tidskrift/Serie: ArcheoSciences
• Volym: 45
• Länkar: http://dx.doi.org/10.4000/archeosciences.10179
• Dokumenttyp: Konferensbidrag
• Ämne: Computer and Information Sciences; Archaeology
• Nyckelord: Airborne LIDAR; Artificial intelligence; Deep neural networks; Feature extraction; Unet
• Aktiv: Published
• Projekt: Under the canopy: reading past agrarian landscapes through the lens of artificial intelligence and remote sensing
• Forskningsgrupp: Digital Archaeology Laboratory DARK Lab
• ISBN/ISSN/Övrigt: ISSN: 1960-1360