FireSOM: AI assisted annotation of acceleration data in Firetail
We are glad to present a new part of our tutorial series on Firetail. This time we talk about „FireSOM: AI assisted annotation“
The most recent Firetail Release 7 includes a AI-based segmentation of acceleration data that allows for the annotation of complete datasets in a few steps. It is our mission to offer a simple and intuitive solution. Especially when the challenges are difficult. The new AI feature has sparked impressive feedback in the community of researchers and species conservationists. Questions about how and why arose. Complex issues are best conveyed with videos. Therefore, the decision to make a tutorial was a no-brainer.
Working with annotations is one of the core features of Firetail. The reason is simple: Annotation of data from tagged animals is essential for conservation and for behavioral analysis. This is particularly challenging given huge amounts of data and long-term experiments. Manual annotation is time-consuming and expensive and near impossible to implement in practice.
In this video we showcase „FireSOM: AI assisted annotation“. A machine learning tool assisting researchers to rapidly annotate massive datasets.
Don’t be scared by machine learning terms like feature selection and self-organizing maps. Embrace them!
