Modified DeepLabV3+ architecture with global context integration and supervised contrastive learning for semantic segmentation of ultra-high-resolution image
Objectives. We propose a modern method for semantic segmentation of ultra-high-resolution (4K) video frames in the field of Earth remote sensing using a modification of the DeepLabV3+ convolutional neural network. Methods. The method is aimed at solving two critical problems: the limited receptive field of the model w...