Convolutional neural network models with low spatial variability hamper the transfer learning process.
- Published in:
- Neural Computing & Applications, 2025, v. 37, n. 19, p. 13927, doi. 10.1007/s00521-025-11267-6
- By:
- Publication type:
- Article
Works by Lopatin, Javier
Results: 7
1
2
Linking plant strategies and plant traits derived by radiative transfer modelling.
- Published in:
- Journal of Vegetation Science, 2017, v. 28, n. 4, p. 717, doi. 10.1111/jvs.12525
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- Publication type:
- Article
3
How canopy shadow affects invasive plant species classification in high spatial resolution remote sensing.
- Published in:
- Remote Sensing in Ecology & Conservation, 2019, v. 5, n. 4, p. 302, doi. 10.1002/rse2.109
- By:
- Publication type:
- Article
4
Disturbance alters relationships between soil carbon pools and aboveground vegetation attributes in an anthropogenic peatland in Patagonia.
- Published in:
- Ecology & Evolution (20457758), 2022, v. 12, n. 3, p. 1, doi. 10.1002/ece3.8694
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- Publication type:
- Article
5
Surviving in a hostile landscape: Nothofagus alessandrii remnant forests threatened by mega-fires and exotic pine invasion in the coastal range of central Chile.
- Published in:
- Oryx, 2023, v. 57, n. 2, p. 228, doi. 10.1017/S0030605322000102
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- Publication type:
- Article
6
Predicting Vascular Plant Diversity in Anthropogenic Peatlands: Comparison of Modeling Methods with Free Satellite Data.
- Published in:
- Remote Sensing, 2017, v. 9, n. 7, p. 681, doi. 10.3390/rs9070681
- By:
- Publication type:
- Article
7
Comparison of carbon and water fluxes and the drivers of ecosystem water use efficiency in a temperate rainforest and a peatland in southern South America.
- Published in:
- Biogeosciences, 2024, v. 21, n. 5, p. 1371, doi. 10.5194/bg-21-1371-2024
- By:
- Publication type:
- Article