Detection of hunting pits using airborne laser scanning and deep learning
SND-ID: 2023-188. Version: 1. DOI: https://doi.org/10.5878/en98-1b29
Associated documentation
Download all files
Citation
Alternative title
Training data for hunting pit detection
Creator/Principal investigator(s)
William Lidberg
- Swedish University of Agricultural Sciences, Forest ecology and management
Research principal
Swedish University of Agricultural Sciences
- Forest ecology and management
Principal's reference number
SLU.seksko.2023.4.4.IÄ-2
Description
The lunar data (1) were used to pre-train a machine learning model before training on the real data of hunting pits from earth (2). The demonstration data was used to visually evaluate the result of the final model.
All code used to create this dataset and train the machine learning models can be found here: https://github.com/williamlidberg/Detection-of-hunting-pits-using-airborne-laser-scanning-and-deep-learning The code is also included in the file "code.zip"
Data contains personal data
No
Language
Unit of analysis
Population
Digitized hunting pits
Sampling procedure
Time period(s) investigated
2022-06-09 – Ongoing
Variables
11
Number of individuals/objects
2519
Data format / data structure
Type of archaeological investigation
Type of archaeological remains
Responsible department/unit
Forest ecology and management
Other research principals
Contributor(s)
Lars Östlund
- Swedish University for Agricultural Sciences, Forest Ecology and Management
Florian Westphal
- Jönköping University, Department of Computing
Camilla Sandström
- Umeå University, Department of Political Science
Funding 1
-
Funding agency:
Marianne and Marcus Wallenberg Foundation
- Project name on the application: Wallenberg AI, Autonomous Systems and Software Program – Humanities and Society (WASP-HS)
- Funding information: The project "Challenges and Social Consequences of Artificial Intelligence in Swedish Forests" in the WASP-HS program
Funding 2
-
Funding agency:
Kempe Foundation
- Project name on the application: Framtidens kartor för klimatanpassad skogsskötsel
Funding 3
-
Funding agency:
Marcus and Amalia Wallenberg Foundation
- Project name on the application: Wallenberg AI, Autonomous Systems and Software Program – Humanities and Society (WASP-HS)
- Funding information: The project "Challenges and Social Consequences of Artificial Intelligence in Swedish Forests" in the WASP-HS program
Research area
Computer science (Standard för svensk indelning av forskningsämnen 2011)
Computer vision and robotics (autonomous systems) (Standard för svensk indelning av forskningsämnen 2011)
Physical geography (Standard för svensk indelning av forskningsämnen 2011)
Geotechnical engineering (Standard för svensk indelning av forskningsämnen 2011)
History (Standard för svensk indelning av forskningsämnen 2011)
Society (INSPIRE topic categories)
