Author/s: Joaquin Cochero, Lorenzo Pattori, Agustín Balsalobre, Soledad Ceccarelli and Gerardo MartiPresenter: Joaquín Cochero
In Geovin we gather information of the distribution of “kissing bugs” (triatomines), that include a vector species of the parasite that causes Chagas disease. The GeoVin app has over 700 registered citizen scientists in Argentina; with the information gathered through this tool, we used a machine-learning approach to train a Convolutional Neural Network (CNN) to recognize true kissing bugs directly from photos taken with cellphone cameras. The CNN reached correct identification rates of 94%, identifying true kissing bugs from other insects even with blurred images, poor lighting or with the presence of other objects in the photo.
Author/s: Sabine Wildevuur, Steven Dorrestijn, Jan Jukema, Kornelia Konrad, Marjolein den Ouden, Frits Oosterveld, Monique Tabak, Renske van Wijk, and Ben KokkelerPresenter: Sabine Wildevuur
Answering complex societal challenges such as the increasing health inequalities between groups of citizens, requires a collaborative approach between citizens as end-users, professionals as facilitators of healthcare and scientists as co-developers of knowledge and innovation. To this end, a consortium in the east of the Netherlands of universities, companies, local and regional government and healthcare organizations has developed the 3 research and innovation program Citizenlab. This is part of the open innovation program TOPFIT that aims to add two healthy years to life expectancy in the next decade. Citizenlab is an environment that allows experimenting with the concept citizen science.
Author/s: Rebeca Silva-Roquefort, Pamela Smith and Valentina ZuñigaPresenter: Rebeca Silva-Roquefort