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T. Gobakken

5 papers hereh-index 6213.5k citations288 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3
  • last author2

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • stat.AP2

identity via Semantic Scholar / OpenAlex

activity
20172026
most citedEstimation of boreal forest biomass from ICESat-2 data using hierarchical hybrid inference

3 citations · 4 across the 4 of their papers we have counts for

collaborators
Showing cs.CVShow all

3 papers · 1 filter

cs.CV2026

Assessing airborne laser scanning and aerial photogrammetry for deep learning-based stand delineation

Håkon Næss Sandum, Hans Ole Ørka, Oliver Tomic +1

Accurate forest stand delineation is essential for forest inventory and management but remains a largely manual and subjective process. A recent study has shown that deep learning…

cs.CV2025★ 1 cited

Semantic segmentation of forest stands using deep learning

Håkon Næss Sandum, Hans Ole Ørka, Oliver Tomic +2

Forest stands are the fundamental units in forest management inventories, silviculture, and financial analysis within operational forestry. Over the past two decades, a common meth…

cs.CV2023

Forest Parameter Prediction by Multiobjective Deep Learning of Regression Models Trained with Pseudo-Target Imputation

Sara Björk, Stian N. Anfinsen, Michael Kampffmeyer +3

In prediction of forest parameters with data from remote sensing (RS), regression models have traditionally been trained on a small sample of ground reference data. This paper prop…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.