Forest Inspection Dataset for Aerial Semantic Segmentation and Depth Estimation

arXiv:2403.06621v1 Announce Type: new
Abstract: Humans use UAVs to monitor changes in forest environments since they are lightweight and provide a large variety of surveillance data. However, their information does not present enough details for understanding the scene which is needed to assess the degree of deforestation. Deep learning algorithms must be trained on large amounts of data to output accurate interpretations, but ground truth recordings of annotated forest imagery are not available. To solve this problem, we introduce a …

abstract aerial algorithms arxiv cs.ai cs.cv data dataset deep learning deep learning algorithms deforestation environments however humans information segmentation semantic surveillance type understanding