This repository contains train and test data sets for building a convolutional neural network model, which is able to recognize different soil/rock formations as well as detect obstacles in a mining / construction environment. This effort is towards the development of smart, autonomous excavators which are able to recognize different excavating environments and adjust the digging strategy accordingly.
GGYIMAH1031/Image_Data_for_Formation_Recognition_-_Obstacle_Detection
This repository contains train and test data sets for building a convolutional neural network model, which is able to recognize different soil/rock formations as well as detect obstacles in a mining / construction environment. This effort is towards the development of smart, autonomous excavators which are able to recognize different excavating environments and adjust the digging strategy accordingly.
Apache-2.0