首页|New Findings in Robotics Described from University of Catania (Terrain Traversab ility Prediction Through Self-supervised Learning and Unsupervised Domain Adapta tion On Synthetic Data)
New Findings in Robotics Described from University of Catania (Terrain Traversab ility Prediction Through Self-supervised Learning and Unsupervised Domain Adapta tion On Synthetic Data)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Fresh data on Robotics are presented i n a new report. According to news originatingfrom Catania, Italy, by NewsRx cor respondents, research stated, “Terrain traversability estimation is afundamenta l task for supporting robot navigation on uneven surfaces. Recent learning-based approachesfor predicting traversability from RGB images have shown promising r esults, but require manual annotationof a large number of images for training.”
CataniaItalyEuropeEmerging Technol ogiesMachine LearningRobotRoboticsSupervised LearningUniversity of Cat ania
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