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

Melda Küçükdemirci; Giacomo Landeschi; Nicolo Dell'Unto; Mattias Ohlsson

doi:10.4000/archeosciences.10179

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

Melda Küçükdemirci, Giacomo Landeschi, Nicolo Dell'Unto, Mattias Ohlsson

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

Sammanfattning

– 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.

Originalspråk	engelska
Titel på värdpublikation	14th International Conference of Archaeological Prospection
Sidor	291-293
Antal sidor	3
Volym	45
Utgåva	1
DOI	https://doi.org/10.4000/archeosciences.10179
Status	Published - 2021

Publikationsserier

Namn	ArcheoSciences
ISSN (tryckt)	1960-1360

Ämnesklassifikation (UKÄ)

Data- och informationsvetenskap
Arkeologi

Tillgång till dokument

10.4000/archeosciences.10179

Under the canopy: reading past agrarian landscapes through the lens of artificial intelligence and remote sensing
Landeschi, G., Kucukdemirci, M., Ohlsson, M., Larsson, M. & Dell'Unto, N.
Projekt: Forskning

Laboratoriet för Digital Arkeologi DARK Lab
Nicolo Dell'unto (Manager) & Martin Hansson (Manager)
Arkeologi
Infrastruktur

Citera det här

@inproceedings{23a4984edd1745e5ba9fdec714d0820e,

title = "Mapping archeological signs from airborne lidar data using deep neural networks: Primary results",

abstract = "– 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.",

keywords = "Airborne LIDAR, Artificial intelligence, Deep neural networks, Feature extraction, Unet",

author = "Melda K{\"u}{\c c}{\"u}kdemirci and Giacomo Landeschi and Nicolo Dell'Unto and Mattias Ohlsson",

year = "2021",

doi = "10.4000/archeosciences.10179",

language = "English",

volume = "45",

series = "ArcheoSciences",

pages = "291--293",

booktitle = "14th International Conference of Archaeological Prospection",

edition = "1",

}

Mapping archeological signs from airborne lidar data using deep neural networks: Primary results. / Küçükdemirci, Melda; Landeschi, Giacomo ; Dell'Unto, Nicolo et al.
14th International Conference of Archaeological Prospection. Vol. 45 1. uppl. 2021. s. 291-293 (ArcheoSciences).

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

TY - GEN

T1 - Mapping archeological signs from airborne lidar data using deep neural networks

T2 - Primary results

AU - Küçükdemirci, Melda

AU - Landeschi, Giacomo

AU - Dell'Unto, Nicolo

AU - Ohlsson, Mattias

PY - 2021

Y1 - 2021

N2 - – 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.

AB - – 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.

KW - Airborne LIDAR

KW - Artificial intelligence

KW - Deep neural networks

KW - Feature extraction

KW - Unet

U2 - 10.4000/archeosciences.10179

DO - 10.4000/archeosciences.10179

M3 - Paper in conference proceeding

AN - SCOPUS:85118757995

VL - 45

T3 - ArcheoSciences

SP - 291

EP - 293

BT - 14th International Conference of Archaeological Prospection

ER -

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

Sammanfattning

Publikationsserier

Ämnesklassifikation (UKÄ)

Tillgång till dokument

Fingeravtryck

Projekt

Under the canopy: reading past agrarian landscapes through the lens of artificial intelligence and remote sensing

Utrustning

Laboratoriet för Digital Arkeologi DARK Lab

Citera det här