Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Gominski, Dimitri"'
Autor:
Gominski, Dimitri, Ortiz-Gonzalo, Daniel, Brandt, Martin, Mugabowindekwe, Maurice, Fensholt, Rasmus
Individual tree species labels are particularly hard to acquire due to the expert knowledge needed and the limitations of photointerpretation. Here, we present a methodology to automatically mine species labels from public forest inventory data, usin
Externí odkaz:
http://arxiv.org/abs/2408.15816
Image-level regression is an important task in Earth observation, where visual domain and label shifts are a core challenge hampering generalization. However, cross-domain regression within remote sensing data remains understudied due to the absence
Externí odkaz:
http://arxiv.org/abs/2405.00514
Autor:
Li, Lei, Zhang, Tianfang, Jiang, Zhongyu, Yang, Cheng-Yen, Hwang, Jenq-Neng, Oehmcke, Stefan, Gominski, Dimitri Pierre Johannes, Gieseke, Fabian, Igel, Christian
Accurate and consistent methods for counting trees based on remote sensing data are needed to support sustainable forest management, assess climate change mitigation strategies, and build trust in tree carbon credits. Two-dimensional remote sensing i
Externí odkaz:
http://arxiv.org/abs/2403.01932
Autor:
Gominski, Dimitri, Kariryaa, Ankit, Brandt, Martin, Igel, Christian, Li, Sizhuo, Mugabowindekwe, Maurice, Fensholt, Rasmus
There is a rising interest in mapping trees using satellite or aerial imagery, but there is no standardized evaluation protocol for comparing and enhancing methods. In dense canopy areas, the high variability of tree sizes and their spatial proximity
Externí odkaz:
http://arxiv.org/abs/2311.07981
Autor:
Carlsen, Ask Holm, Fensholt, Rasmus, Looms, Majken Caroline, Gominski, Dimitri, Stisen, Simon, Jepsen, Martin Rudbeck
Publikováno v:
In Agricultural Water Management 30 June 2024 299
With impressive results in applications relying on feature learning, deep learning has also blurred the line between algorithm and data. Pick a training dataset, pick a backbone network for feature extraction, and voil\`a ; this usually works for a v
Externí odkaz:
http://arxiv.org/abs/2103.10729
Advances in high resolution remote sensing image analysis are currently hampered by the difficulty of gathering enough annotated data for training deep learning methods, giving rise to a variety of small datasets and associated dataset-specific metho
Externí odkaz:
http://arxiv.org/abs/2102.13392
This article proposes to study the behavior of recent and efficient state-of-the-art deep-learning based image descriptors for content-based image retrieval, facing a panel of complex variations appearing in heterogeneous image datasets, in particula
Externí odkaz:
http://arxiv.org/abs/1909.08866
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