U-net is an image segmentation technique developed primarily for image segmentation
tasks. These traits provide U-net with a high utility within the medical imaging community …

Minimally invasive surgical instrument visual detection and tracking is one of the core
algorithms of minimally invasive surgical robots. With the development of machine vision …

Data augmentation is a commonly used technique for increasing both the size and the
diversity of labeled training sets by leveraging input transformations that preserve …

Building footprint extraction is a basic task in the fields of map**, image understanding,
computer vision, and so on. Accurately and efficiently extracting building footprints from a …

Automatic instrument segmentation in video is an essentially fundamental yet challenging
problem for robot-assisted minimally invasive surgery. In this paper, we propose a novel …

Automatic surgical instrument segmentation is a necessary step for the steady operation of
surgical robots, and the segmentation accuracy directly affects the surgical effect …

This is a review focused on advances and current limitations of computer vision (CV) and
how CV can help us obtain to more autonomous actions in surgery. It is a follow-up article to …

Ubiquitous finger motion tracking enables a number of exciting applications in augmented
reality, sports analytics, rehabilitation-healthcare, haptics etc. This paper presents …

The state-of-the-art deep learning methods have demonstrated impressive performance in
segmentation tasks. However, the success of these methods depends on a large amount of …

UNet adopting an encoder-decoder structure has been used widely in medical image
segmentation tasks for its outstanding performance. However, in our work, we find that UNet …