ShorelineNet: An Efficient Deep Learning Approach for Shoreline Semantic Segmentation for Unmanned Surface Vehicles
Linghong Yao,Dimitrios Kanoulas,Ze Ji,Yuanchang Liu,Linghong Yao,Dimitrios Kanoulas,Ze Ji,Yuanchang Liu
This paper introduces a novel deep learning approach to semantic segmentation of the shoreline environments with a high frames-per-second (fps) performance, making the approach readily applicable to autonomous navigation for Unmanned Surface Vehicles (USV). The proposed ShorelineNet is an efficient deep neural network of high performance relying only on visual input. ShorelineNet uses monocular vi...
