Application progress of artificial intelligence in traditional Chinese medicine nursing

Abstract

3D Morphable Models (3DMMs) provide promising 3D face reconstructions in various applications. However, existing methods struggle to reconstruct faces with extreme expressions due to deficiencies in supervisory signals, such as sparse or inaccurate landmarks. Segmentation information contains effective geometric contexts for face reconstruction. Certain attempts intuitively depend on differentiable renderers to compare the rendered silhouettes of reconstruction with segmentation, which is prone to issues like local optima and gradient instability. In this paper, we fully utilize the facial part segmentation geometry by introducing Part Re-projection Distance Loss (PRDL). Specifically, PRDL transforms facial part segmentation into 2D points and re-projects the reconstruction onto the image plane. Subsequently, by introducing grid anchors and computing different statistical distances from these anchors to the point sets, PRDL establishes geometry descriptors to optimize the distribution of the point sets for face reconstruction. PRDL exhibits a clear gradient compared to the renderer-based methods and presents state-of-the-art reconstruction performance in extensive quantitative and qualitative experiments. The project will be publicly available.

Performance evaluation of a traditional Chinese medicine massage robot based on multi-information fusion

“…The massage robot is a type of service robot, and many countries have conducted related research [13], [14]. Massage technology is more mature, and massage robots have also been designed and developed [15], [16] for applications in stroke rehabilitation [17], lower limb rehabilitation [18], facial disease rehabilitation [19], back massage [20], and other areas.…”