Zobrazeno 1 - 10
of 2 833
pro vyhledávání: '"P. Astrup"'
In this paper we present new results about arrangements of lines and conics associated to the Fermat curves in the projective plane. The first result is that we compute the 2-Hessian to a Fermat curve, which is a union of lines, and we determine the
Externí odkaz:
http://arxiv.org/abs/2412.16993
This paper presents an automated pipeline for detecting tree whorls in proximally laser scanning data using a pose-estimation deep learning model. Accurate whorl detection provides valuable insights into tree growth patterns, wood quality, and offers
Externí odkaz:
http://arxiv.org/abs/2409.14755
Autor:
Puliti, Stefano, Lines, Emily R., Müllerová, Jana, Frey, Julian, Schindler, Zoe, Straker, Adrian, Allen, Matthew J., Winiwarter, Lukas, Rehush, Nataliia, Hristova, Hristina, Murray, Brent, Calders, Kim, Terryn, Louise, Coops, Nicholas, Höfle, Bernhard, Junttila, Samuli, Krůček, Martin, Krok, Grzegorz, Král, Kamil, Levick, Shaun R., Luck, Linda, Missarov, Azim, Mokroš, Martin, Owen, Harry J. F., Stereńczak, Krzysztof, Pitkänen, Timo P., Puletti, Nicola, Saarinen, Ninni, Hopkinson, Chris, Torresan, Chiara, Tomelleri, Enrico, Weiser, Hannah, Astrup, Rasmus
Proximally-sensed laser scanning offers significant potential for automated forest data capture, but challenges remain in automatically identifying tree species without additional ground data. Deep learning (DL) shows promise for automation, yet prog
Externí odkaz:
http://arxiv.org/abs/2408.06507
Publikováno v:
Remote Sensing of Environment, Volume 313, 2024, 114367, ISSN 0034-4257
This research advances individual tree crown (ITC) segmentation in lidar data, using a deep learning model applicable to various laser scanning types: airborne (ULS), terrestrial (TLS), and mobile (MLS). It addresses the challenge of transferability
Externí odkaz:
http://arxiv.org/abs/2401.15739
Autor:
Xiang, Binbin, Wielgosz, Maciej, Kontogianni, Theodora, Peters, Torben, Puliti, Stefano, Astrup, Rasmus, Schindler, Konrad
Detailed forest inventories are critical for sustainable and flexible management of forest resources, to conserve various ecosystem services. Modern airborne laser scanners deliver high-density point clouds with great potential for fine-scale forest
Externí odkaz:
http://arxiv.org/abs/2312.15084
Autor:
Khaksar, Weria, Astrup, Rasmus
Forests, as critical components of our ecosystem, demand effective monitoring and management. However, conducting real-time forest inventory in large-scale and GNSS-interrupted forest environments has long been a formidable challenge. In this paper,
Externí odkaz:
http://arxiv.org/abs/2310.01064
Autor:
Puliti, Stefano, Pearse, Grant, Surový, Peter, Wallace, Luke, Hollaus, Markus, Wielgosz, Maciej, Astrup, Rasmus
The FOR-instance dataset (available at https://doi.org/10.5281/zenodo.8287792) addresses the challenge of accurate individual tree segmentation from laser scanning data, crucial for understanding forest ecosystems and sustainable management. Despite
Externí odkaz:
http://arxiv.org/abs/2309.01279
Publikováno v:
Tidsskrift for boligforskning, Vol 7, Iss 2, Pp 149-151 (2024)
Externí odkaz:
https://doaj.org/article/61792171c3cd40aa97349a6a4090bcb7
Autor:
Xiang, Binbin, Peters, Torben, Kontogianni, Theodora, Vetterli, Frawa, Puliti, Stefano, Astrup, Rasmus, Schindler, Konrad
Panoptic segmentation is the combination of semantic and instance segmentation: assign the points in a 3D point cloud to semantic categories and partition them into distinct object instances. It has many obvious applications for outdoor scene underst
Externí odkaz:
http://arxiv.org/abs/2307.02877
This article introduces Point2Tree, a novel framework that incorporates a three-stage process involving semantic segmentation, instance segmentation, optimization analysis of hyperparemeters importance. It introduces a comprehensive and modular appro
Externí odkaz:
http://arxiv.org/abs/2305.02651