allow autonomous machines to execute field operations in crops. However, for obtaining
high performances, these methods need high amounts of data, which are usually scarce in
agriculture. The main reason is that building an agricultural dataset covering exhaustively a
specific problem is challenging, as visual characteristics of the symptoms may change, and
there is a high dependency on environmental factors, such as temperature, humidity and …