首页|Research Data from Shanghai Jiao Tong University Update Understanding of Machine Learning (Residual Stress-driven Non-euclidean Morphing In Origami Structures)
Research Data from Shanghai Jiao Tong University Update Understanding of Machine Learning (Residual Stress-driven Non-euclidean Morphing In Origami Structures)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news reporting originating from Shanghai, People’s Repu blic of China, by NewsRx correspondents, research stated, “Morphing origami has numerous potential engineering applications owing to its intrinsic morphing feat ures from 2D planes to 3D surfaces. However, the current 1D hinge deformation-dr iven transformation of foldable origami with rigid or slightly deformable panels cannot achieve a 3D complex and large curvilinear morphing.”
ShanghaiPeople's Republic of ChinaAs iaMachine LearningShanghai Jiao Tong University
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