We present a Deep Learning based system for the twin tasks of localization and obstacle avoidance essential to any mobile robot. Our system learns from conventional geometric SLAM, and outputs, using a single camera, the topological pose of the camera in an environment, and the depth map of obstacles around it. We use a CNN to localize in a topological map, and a conditional VAE to output depth for a camera image, conditional on this topological location estimation. We demonstrate the effectiveness of our monocular localization and depth estimation system on simulated and real datasets.
Small Activating RNA Modulation
In article number 2200562, Ling Peng, Leo Tsz On Lee, and co‐workers, report for the first time that small activating RNA (saRNA) delivered by amphiphilic dendrimer can effectively modulate a G protein‐coupled receptors (GPCR), Mas receptor, for cancer treatment. This project provides not only a new strategy for cancer therapy, but also a new avenue to address undruggable GPCRs.
In this paper, we demonstrate a system that automates the process of recording video lectures in classrooms. Through special hardware (lecturer and audience facing cameras and microphone arrays), we record multiple points of view of the lecture. Person detection and tracking, along with recognition of different human actions are used to digitally zoom in on the lecturer, and alternate focus between the lecturer and the slides or the blackboard. Audio sound source localization, along with face detection and tracking, is used to detect questions from the audience, to digitally zoom in on the member of the audience asking the question and to improve the quality of the sound recording. Finally, an automatic video editing system is used to naturally switch between the different video streams and to compose a compelling end product. We demonstrate the working system in two classrooms, over two 2-hour lectures, given by two lecturers.
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