Citizen Science and Machine Learning for Research and Nature
  Conservation: The Case of Eurasian Lynx, Free-ranging Rodents and Insects
Kinga Skorupska Rafał Stryjek Izabela Wierzbowska Piotr Bebas Maciej Grzeszczuk Piotr Gago Jarosław Kowalski Maciej Krzywicki Jagoda Lazarek Wiesław Kopeć
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.