Mariana Belgiu

Deep learning algorithms can achieve great accuracies, but there are also concerns about biases and generalizability to unseen data.

With the increasing availability of remotely sensed data, there is a pressing need to develop efficient and scalable methods for converting satellite images into useful information.

The challenge of this topic is to detect a change or trend on top of seasonal fluctuations.

Farmers, agronomists, private enterprise and policy-makers need to know field conditions with sufficient early-warning.