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Found 6 papers, 2 papers with code
ShadowSense: Unsupervised Domain Adaptation and Feature Fusion for Shadow-Agnostic Tree Crown Detection from RGB-Thermal Drone Imagery
Accurate detection of individual tree crowns from remote sensing data poses a significant challenge due to the dense nature of forest canopy and the presence of diverse environmental variations, e. g., overlapping canopies, occlusions, and varying lighting conditions.
Training-based Model Refinement and Representation Disagreement for Semi-Supervised Object Detection
Extensive experiments demonstrate the superior performance of our approach over state-of-the-art SSOD methods.
Crown-CAM: Interpretable Visual Explanations for Tree Crown Detection in Aerial Images
Visual explanation of ``black-box'' models allows researchers in explainable artificial intelligence (XAI) to interpret the model's decisions in a human-understandable manner.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Early Detection of Bark Beetle Attack Using Remote Sensing and Machine Learning: A Review
This paper provides a comprehensive review of past and current advances in the early detection of bark beetle-induced tree mortality from three primary perspectives: bark beetle & host interactions, RS, and ML/DL.
Classification of Bark Beetle-Induced Forest Tree Mortality using Deep Learning
Bark beetle outbreaks can dramatically impact forest ecosystems and services around the world.
Learning-based Monocular 3D Reconstruction of Birds: A Contemporary Survey
In nature, the collective behavior of animals, such as flying birds is dominated by the interactions between individuals of the same species.
