A Review on different ML Techniques used for Disease Detection in Sugarcane Crop

Latest improvements in precision agriculture through machine learning, deep remote sensing has helped to come up with different methods detect crop diseases. One of the main reasons for yield loss a is non detection disease early time. This paper reviews various and techniques that can be used diseases sugarcane crop. Firstly, we provide review on types input data w.r.t imagery -RGB, multispectral hyperspectral. Then highlight applied detection-machine transfer learning spectral information divergence. We also give an overview results achieved by using techniques.