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Lassi Ruoppa

3 papers here

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  • cs.CV2
  • eess.IV1

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collaborators

3 papers

cs.CV2025

Benchmarking individual tree segmentation using multispectral airborne laser scanning data: the FGI-EMIT dataset

Lassi Ruoppa, Tarmo Hietala, Verneri Seppänen +6

Individual tree segmentation (ITS) from LiDAR point clouds is fundamental for applications such as forest inventory, carbon monitoring and biodiversity assessment. Traditionally, I…

eess.IV2025

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

Narges Takhtkeshha, Lauris Bocaux, Lassi Ruoppa +4

Conservation and decision-making regarding forest resources necessitate regular forest inventory. Light detection and ranging (LiDAR) in laser scanning systems has gained significa…

cs.CV2025

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

Lassi Ruoppa, Oona Oinonen, Josef Taher +5

Point clouds captured with laser scanning systems from forest environments can be utilized in a wide variety of applications within forestry and plant ecology, such as the estimati…

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