Lichens are unique organisms, valued for their pharmacological activity, but also well known as bioindicators of environmental pollution, key determinants for some natural ecological habitats, or just popular elements of decoration. High morphological similarity between lichen species makes their recognition complicated, especially under in-field conditions. Thus, there is a need for a quick and easy method that can help with the preliminary classification of selected lichen species. This paper presents a tool that can facilitate the recognition of Cladonia lichen species, based on a deep convolutional neural network, a model which has nowadays reached a classification level often comparable to humans. The network was trained and tested on twelve Cladonia species using a total of 1164 images, downloaded from various websites. The trained model achieved 60.94% accuracy, which is satisfactory for this novel, but still preliminary, automated classification of lichen species.

地衣是独特的生物，因其药理作用而受到重视，但也众所周知是环境污染的生物指示剂，某些自然生态栖息地的关键决定因素或仅仅是流行的装饰元素。地衣物种之间的高度形态相似性使其识别变得复杂，尤其是在田间条件下。因此，需要一种快速简便的方法，该方法可以帮助所选地衣物种的初步分类。本文提出了一种工具，该工具可基于深层卷积神经网络（该模型如今已达到通常可与人类媲美的分类水平），促进识别Cladonia地衣物种。该网络已在12个Cladonia上进行了培训和测试物种共使用了1164张图像，这些图像可从各个网站下载。经过训练的模型达到了60.94％的准确度，对于这种新颖但仍是自动的地衣物种自动分类而言，这是令人满意的。