Machine Learning Training for Automatic Target Detection

This blog offers a deeper dive into the machine learning training process for performing automatic target detection. Samples of automatic target detection were recently presented at the Machine Learning: Automate Remote Sensing Analytics to Gain a Competitive Advantage webinar. Machine learning (ML) applications, from object recognition and caption generation, to automatic language translation and driverless cars, have increased dramatically over the last few years, powered mainly by the increase of computing power (using GPUs), reduced cost of storage, wider availability of training data, and development of new training techniques for the machine learning models. In the last five years, Harris Corporation has made a multi-million dollar investment into applying machine learning to solve customer challenges using remote sensing data. In response to the increased interest from our customers in evaluating how machine learning can solve their problems using geospatial data, I set out to train some of my coworkers on how to build a ML model to perform automatic feature detection on 2D overhead imagery.