Advantages and Bottlenecks of Quantum Machine Learning for Remote Sensing

Building on recent theoretical proposals, classification techniques, so focusing on remote sensing applications, initial practical studies suggest that these concepts have the and discuss the bottlenecks of performing these algorithms possibility to be implemented in the laboratory, under strictly on currently available open source platforms. Initial controlled conditions [4], and open the way to the evolution results demonstrate feasibility. Next steps include expanding of their employment and validation.