In Deep Learning, identification of different tree species is a challenging task due to the diversity and complexity of growing environment. The task becomes more difficult in case of classifying rare tree species where the available training data is insufficient. Here we utilize a recent convolutional neural network architecture for classifying tree species using remote sensing data provided as part of the IDTReeS competition. The prebuilt model successfully delineated individual tree crowns from RGB imagery.