How Artificial Intelligence Estimates Obesity Levels From Google Map Photos

In a recent study, two researchers at the University of Washington used deep learning techniques to estimate obesity levels in 6 US cities. Adyasha Maharana and Dr. Elaine Okanyene Nsoesie used a convolutional neural network to extract information from Google Maps images which they found had a close relationship with obesity levels in the area. Features extracted by the convolutional neural network. The network seems to focus on natural features such as lakes and parks.Adyasha Maharana; Elaine Okanyene Nsoesie. The research suggests that the predictive power for obesity rates came from the presence of natural features such as lakes and parks detected by the neural network. The left side shows the true obesity rates from the Behavioral Risk Factor Surveillance System.