Babak Taati

TL;DR: The Difference of Normals (DoN) provides a computationally efficient, multi-scale approach to processing large unorganized 3D point clouds and is shown to segment large 3Dpoint clouds into scale-salient clusters towards applications in semi-automatic annotation, and as a pre-processing step in automatic object recognition.

TL;DR: A signal processing approach equipped with a machine learning paradigm is implemented to process and analyze real-world data acquired using home-based unobtrusive sensing technologies to autonomously detect mild cognitive impairment in older adults.

TL;DR: A generalized platform for constructing local shape descriptors that subsumes a large class of existing methods, and that allows for tuning to the geometry of specific models is presented.

TL;DR: In this paper, the authors present automated emergency detection and response systems and methods, in accordance with different embodiments of the invention, in some embodiments, respective data sets generated in respect of distinctly located sensors are compared, and an appropriate response protocol is selected based on this comparison and as a function of at least one of the data sets.

TL;DR: The proposed system provides insight into the potential of computer vision and deep learning for clinical application in PD and demonstrates promising performance for the future translation of deep learning to PD clinical practices.