Tree Species Identification Based on Convolutional Neural Networks

The article provides an effective approach to automatically identify tree species using convolutional neural networks (CNNs). The work identifies tree species by analyzing tree leaves, which have multi-dimensional features such as color, shape, and leaf vein signatures. Since it is difficult to find a single leaf feature to accurately identify tree species, convolutional neural networks are employed to integrate multi-dimensional leaf features. Additional preprocessing steps are employed to increase the robustness of the identification results. This approach is evaluated based on the Leafsnap database and achieves satisfying performance.