首页|Investigators from Northeastern University Report New Data on Robotics (Robot Unknown Objects Instance Segmentation Based On Collaborative Weight Assignment Rgb-depth Fusion Strategy)
Investigators from Northeastern University Report New Data on Robotics (Robot Unknown Objects Instance Segmentation Based On Collaborative Weight Assignment Rgb-depth Fusion Strategy)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Robotics are discussed in a new report. According to newsreporting originating in Shenyang, People’s Republic of China, by NewsRx journalists, research stated,“Unknown objects instance-aware segmentation (UOIS) is crucial for the operation of autonomous robots,especially in unstructured scenes with unknown objects. As the primary data source types for robots, RGBand Depth are not fully exploited by existing studies due to the inherent information differences betweenRGB (2-D appearance) and Depth (3-D geometry).”
ShenyangPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningNano-robotRobotRoboticsNortheastern University
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