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Tree species identification using bark images is a challenging problem that could prove useful for many forestry related tasks. However, while the recent progress in deep learning showed impressive results on standard vision problems, a lack of datasets prevented its use on tree bark species classification. In this work, we present, and make public...
Tree species identification using images of the bark is a challenging problem that could help in tasks such as drone navigation in forest environment and autonomous forest inventory management. It also brings more value to harvesting operations as it leads to greater market values of trees. While the recent progress in deep learning showed its effe...
The goal of the project is to partially automate logging and forestry operations, to amplify human control and productivity. We aim at employing state-of-the-art algorithms from mobile robotics (SLAM, Navigation, LiDAR) and machine learning to reach this goal.