“Research by Apple Inc. computer scientists on how self-driving cars can better spot cyclists and pedestrians while using fewer sensors has been posted online, in what appears to be the company’s first publicly disclosed paper on autonomous vehicles,” Stephen Nellis reports for Reuters.

“The paper by Yin Zhou and Oncel Tuzel, submitted on Nov. 17 to independent online journal arXiv, is significant because Apple’s famed corporate secrecy around future products has been seen as a drawback among artificial intelligence and machine learning researchers,” Nellis reports. “The scientists proposed a new software approach called ‘VoxelNet’ for helping computers detect three-dimensional objects.”

“Self-driving cars often use a combination of normal two-dimensional cameras and depth-sensing ‘LiDAR’ units to recognize the world around them. While the units supply depth information, their low resolution makes it hard to detect small, faraway objects without help from a normal camera linked to it in real time,” Nellis reports. “But with new software, the Apple researchers said they were able to get ‘highly encouraging results’ in spotting pedestrians and cyclists with just LiDAR data.”

Read more in the full article here.

MacDailyNews Note: The research paper, “VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection,” is located here.

SEE ALSO:
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