Technology is increasingly used in Nature Reserves and National Parks around
the world to support conservation efforts. Endangered species, such as the
Eurasian Lynx (Lynx lynx), are monitored by a network of automatic photo traps.
Yet, this method produces vast amounts of data, which needs to be prepared,
analyzed and interpreted. Therefore, researchers working in this area
increasingly need support to process this incoming information. One opportunity
is to seek support from volunteer Citizen Scientists who can help label the
data, however, it is challenging to retain their interest. Another way is to
automate the process with image recognition using convolutional neural
networks. During the panel, we will discuss considerations related to nature
research and conservation as well as opportunities for the use of Citizen
Science and Machine Learning to expedite the process of data preparation,
labelling and analysis.

网络技术在自然保护区和国家公园中的应用越来越普遍，用于支持保护工作。通过自动照片陷阱网络对濒危物种如欧亚山猫（Lynx lynx）进行监测，但该方法产生了大量需要准备、分析和解释的数据。因此，研究人员在这个领域越来越需要处理来自这些数据的支持。一种机会是寻求来自志愿公众科学家的支持，他们可以帮助标记数据，然而，保留他们的兴趣是具有挑战性的。另一种方法是使用卷积神经网络进行图像识别自动化处理。在本研究中，我们将讨论与自然研究和保护相关的考虑事项，以及利用公众科学和机器学习加快数据准备、标注和分析过程的机会。