Image Processing

A research group from the university of California used Neuronal Networks for EDGE detection: github repository, see paper below.

They used Caffe Deep learning framework. The same concepts can be applied to our case, maybe using Caffe2. NOTE: the alternative would be TensorFlow, but the mobile deployment is too heavy for the old raspberry PI and needs a huge SD card, see here, meanwhile it should be easier with Caffe2, see here.

So basically we need an Image to Image neural network that recognizes the parts of the agricultural fields black and the rest white (or the opposite). To simplify the training of the network it could be a good idea to develop an iterative image recognition algorithm, based on color, texture, ... first and use it to provide learning data with google maps. The automatically elaborated pictures can then just be corrected with human interaction (smooth workflow needed!) to provide the needed gain in quality.