Compact, Scalable Lidar Design Could Boast Applications Spanning Robotics, Health Care
Researchers from the University of Southampton, in collaboration with a team from San Francisco-based nanotechnology company PointCloud Inc., developed a scalable 3D lidar imaging system that the collaborators said matches and exceeds the performance and accuracy of most mechanical systems currently in use. The cost-effective device may provide a path to large-volume production of compact, inexpensive, and high-performance 3D imaging cameras for use in robotics, autonomous navigation systems, mapping of building sites to increase safety, and health care.
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Research from Lawrence Livermore National Laboratory (LLNL) has yielded a method of compressive image recovery that is trained on patches of images, rather than full-size images. The method, called GPP (generative patch prior), is able to recover a wide variety of natural images. It compares favorably with other existing methods, the researchers said, in its ability to perform compressive image sensing and complete compressive phase retrieval tasks.
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Skoltech (Russia) scientists are working to combine machine vision with an artificial nose to ensure the proper level of doneness for cooked chicken. The technology aims to help restaurants monitor and automate cooking processes.
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