Gu Jia

TL;DR: A novel self-supervised depth estimation network is proposed that outperforms the state-of-the-art approaches of depth estimation and uses quadtree-based Photometric loss, which calculates the averaged photometric loss in quadtree blocks instead of the pixel-wise loss.

TL;DR: This paper presents a novel CCTA image segmentation framework that combines deep learning and digital image processing algorithms to address these challenging problems and shows that the method is better than the mainstream baseline.

TL;DR: A novel global feature embedded network for better coronary arteries segmentation in 3D coronary computed tomography angiography (CTA) data is proposed, which contains semantic information and detailed features, aiming to accurately segment target with precise boundary.

TL;DR: A depth network of contour and gradient attention is proposed, which is used to complete and correct depth maps to obtain high-resolution and high-quality depth maps and significantly improves the quality of the depth maps, the localization results, and the effect of 3D reconstruction.

TL;DR: In this article, a man-machine interaction intelligent robot dog with four legs, a neck, a trunk, a head, a tail and a control system, the control system comprises a motion control module, a detection module, information output module, communication module, positioning navigation module and a power module and the communication module is further in bidirectional connection with a household appliance control module.