Iban Berganzo Besga

Berganzo-Besga, I., Orengo, H., Canela, J., & Belarte, M. (2022). Potential of Multitemporal Lidar for the Detection of Subtle Archaeological Features under Perennial Dense Forest. Land, 11, 1964. https://doi.org/10.3390/land11111964

Berganzo-Besga, I., Orengo, H., Lumbreras, F., Alam, A., Campbell, R., Gerrits, P., Gregorio de Souza, J., Khan, A., Suárez-Moreno, M., Tomaney, J., Roberts, R., & Petrie, C. (2023). Curriculum learning-based strategy for low-density archaeological mound detection from historical maps in India and Pakistan. Scientific Reports, 13, 11257. https://doi.org/10.1038/s41598-023-38190-x

Berganzo-Besga, I., Orengo, H., Lumbreras, F., Aliende, P., & Ramsey, M. (2022). Automated Detection and Classification of Multi-Cell Phytoliths Using Deep Learning-Based Algorithms. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4115214

Berganzo-Besga, I., Orengo, H., Lumbreras, F., Carrero-Pazos, M., Fonte, J., & Vilas-Estévez, B. (2021). Hybrid MSRM-Based Deep Learning and Multitemporal Sentinel 2-Based Machine Learning Algorithm Detects Near 10k Archaeological Tumuli in North-Western Iberia. Remote Sensing, 13, 4181. https://doi.org/10.3390/rs13204181

Orengo, H., Berganzo-Besga, I., Landauer, J., Aliende, P., Tres-Martínez, S., & Garcia-Molsosa, A. (2021). New developments in drone-based automated surface survey: Towards a functional and effective survey system. Archaeological Prospection, 28, 1–8. https://doi.org/10.1002/arp.1822