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Help us build a database of insects in the Swiss Alps and train AI for automated pollinator monitoring!
Learn moreYou will be presented with a flipbook of up to 5 images taken with our field cameras and asked to identify the insects into broad categories. Drawing a rectangle around the insect in the picture will help us to cut busy backgrounds out so that we can train our AI to identify just the insects of interest.
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Message from the researcher
Automated insect monitoring can revolutionize how we study pollination. With sharp declines in insect populations and global climate change, we need to quickly advance our understanding of interactions to predict and mitigate negative effects.
Luca PegoraroAbout Alpine Bug Shot
Machine learning (ML) and artificial intelligence (AI) are becoming increasingly important tools across many disciplines, ecology not excluded. Whereas these tools are (relatively) easily implemented for large, easily identifiable subjects such as mammals, there is still much to be desired in the realm of insect detection and identification. Some challenges we face are small, highly mobile subjects with complex, moving backgrounds, which make it difficult to automatically detect whether an image includes an insect or not. Thanks to the power of community science through Zooniverse, we are hoping to get a first round of annotations for our collection of insect images collected in the Swiss Alps, which we will then be able to use to train a ML model. Ultimately, we hope to have enough annotated data to train our model to automatically detect and roughly identify the insects visiting our flowers, after which we can begin to understand the biodiversity and interaction networks in our system.
Thank you for helping us with this huge undertaking!!!
