Search Results for author:
Found 2 papers, 2 papers with code
Data-driven Crop Growth Simulation on Time-varying Generated Images using Multi-conditional Generative Adversarial Networks
A prerequisite for realistic and sharp crop image generation is the integration of multiple growth-influencing conditions in a model, such as an image of an initial growth stage, the associated growth time, and further information about the field treatment.
Exploring Wilderness Characteristics Using Explainable Machine Learning in Satellite Imagery
Occluding certain activations in an interpretable artificial neural network we complete a comprehensive sensitivity analysis regarding wild and anthropogenic characteristics.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
