Zobrazeno 1 - 10
of 1 962
pro vyhledávání: '"A. Puliti"'
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
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:
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
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
Autor:
Lines, Emily R., Allen, Matt, Cabo, Carlos, Calders, Kim, Debus, Amandine, Grieve, Stuart W. D., Miltiadou, Milto, Noach, Adam, Owen, Harry J. F., Puliti, Stefano
With the rise in high resolution remote sensing technologies there has been an explosion in the amount of data available for forest monitoring, and an accompanying growth in artificial intelligence applications to automatically derive forest properti
Externí odkaz:
http://arxiv.org/abs/2212.09937
Publikováno v:
BioTechniques, Vol 29, Iss 5, Pp 1012-1017 (2000)
In this report, we present a fluorescencebased approach to the assessment of cellular gene expression and transcription rates. Nuclear run-on was performed by supplying biotin-16-UTP to nuclei, and labeled transcripts were bound to streptavidin-coate
Externí odkaz:
https://doaj.org/article/0eaa72cb9f724868a3c6f5638f18d3cd
Autor:
Maria Benevolo, Guglielmo Ronco, Pamela Mancuso, Francesca Carozzi, Laura De Marco, Elena Allia, Simonetta Bisanzi, Raffaella Rizzolo, Daniela Gustinucci, Annarosa Del Mistro, Helena Frayle, Massimo Confortini, Jessica Viti, Anna Iossa, Elena Cesarini, Simonetta Bulletti, Basilio Passamonti, Silvia Gori, Laura Toniolo, Laura Bonvicini, Francesco Venturelli, Nicolas Wentzensen, Paolo Giorgi Rossi, Alessandra Barca, Francesco Quadrino, Francesca Rollo, Gabriele Carlinfante, Teresa Rubino, Francesca Maria Carozzi, Cristina Sani, Andrea Baldini, Giampaolo Pompeo, Alessandra Mongia, Giulia Fantacci, Donella Puliti, Carmelina Di Pierro, Luigia Macrì, Teresa Pusiol, Mattia Barbareschi, Emma Bragantini, Gabriella Penon, Natalina Marchi, Manuel Zorzi, Elena Narne, Anna Turrin
Publikováno v:
EBioMedicine, Vol 104, Iss , Pp 105149- (2024)
Summary: Background: Each high-risk HPV genotype has different oncogenic potential, and the risk of CIN3+ varies according to genotype. We evaluated the performance of different strategies of HPV-positivity triage combining cytology, p16/ki67 dual st
Externí odkaz:
https://doaj.org/article/df47ce806f6a4e56806a32adf4fd47a0