Narges Takhtkeshha

According to our database, Narges Takhtkeshha authored at least 6 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

3D forest semantic segmentation using multispectral LiDAR and 3D deep learning.

Narges Takhtkeshha, Lauris Bocaux, Lassi Ruoppa, Fabio Remondino, Gottfried Mandlburger, Antero Kukko, Juha Hyyppä

CoRR, July, 2025

Multispectral airborne laser scanning for tree species classification: a benchmark of machine learning and deep learning algorithms.

Josef Taher, Eric Hyyppä, Matti Hyyppä, Klaara Salolahti, Xiaowei Yu, Leena Matikainen, Antero Kukko, Matti Lehtomäki, Harri Kaartinen, Sopitta Thurachen, Paula Litkey, Ville Luoma, Markus Holopainen, Gefei Kong, Hongchao Fan, Petri Rönnholm, Antti Polvivaara, Samuli Junttila, Mikko Vastaranta, Stefano Puliti, Rasmus Astrup, Joel Kostensalo, Mari Myllymäki, Maksymilian Kulicki, Krzysztof Sterenczak, Raul de Paula Pires, Ruben Valbuena, Juan Pedro Carbonell-Rivera, Jesús Torralba, Yi-Chen Chen, Lukas Winiwarter, Markus Hollaus, Gottfried Mandlburger, Narges Takhtkeshha, Fabio Remondino, Maciej Lisiewicz, Bartlomiej Kraszewski, Xinlian Liang, Jianchang Chen, Eero Ahokas, Kirsi Karila, Eugeniu Vezeteu, Petri Manninen, Roope Näsi, Heikki Hyyti, Siiri Pyykkönen, Peilun Hu, Juha Hyyppä

CoRR, April, 2025

Unsupervised deep learning for semantic segmentation of multispectral LiDAR forest point clouds.

Lassi Ruoppa, Oona Oinonen, Josef Taher, Matti Lehtomäki, Narges Takhtkeshha, Antero Kukko, Harri Kaartinen, Juha Hyyppä

CoRR, February, 2025

2024

Multispectral Light Detection and Ranging Technology and Applications: A Review.

Narges Takhtkeshha, Gottfried Mandlburger, Fabio Remondino, Juha Hyyppä

Sensors, March, 2024

Automatic Annotation Of 3D Multispectral LiDAR Data For Land Cover Classification.

Narges Takhtkeshha, Onur Can Bayrak, Gottfried Mandlburger, Fabio Remondino, Antero Kukko, Juha Hyyppä

Proceedings of the IGARSS 2024, 2024

2023

A Rapid Self-Supervised Deep-Learning-Based Method for Post-Earthquake Damage Detection Using UAV Data (Case Study: Sarpol-e Zahab, Iran).

Narges Takhtkeshha, Ali Mohammadzadeh, Bahram Salehi

Remote. Sens., January, 2023