3 accepted papers
This paper addresses the challenge of training a single network to jointly perform multiple dense prediction tasks, such as segmentation and depth estimation, i.e., multi-task learning (MTL). Current approaches mainly capture cross-task relations in the 2D image space, often leading to unstructured
Keypoints-based approaches have shown to be promising for retinal image registration, which superimpose two or more images from different views based on keypoint detection and description. However, existing approaches suffer from ineffective keypoint detector and descriptor training. Meanwhile, the…
In this paper, we present a sparsity-based space-time adaptive processing (STAP) algorithm with coprime array and coprime pulse repetition interval (PRI). The considered space-time coprime configuration can significantly save the cost. However, the direct STAP does not exploit the advantage of the l…