24 Patents
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- US123079902025Microfluidic Pixel Driving Circuit, Microfluidic Substrate, and Microfluidic Chip
Shanghai Tianma Microelectronics Co., Ltd.
0 cites - US122267712025Driving Circuit, Driving Method and Microfluidic Substrate
Shanghai Tianma Micro-electronics Co., Ltd.
0 cites - US122269202025System(s) and Method(s) of Using Imitation Learning in Training and Refining Robotic Control Policies
GOOGLE LLC
0 cites - US122031312025Gene Sequencing Structure, Gene Sequencing Device and Gene Sequencing Method
Shanghai Tianma Micro-electronics Co., Ltd.
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- US121653472024Robotic Control Based on 3D Bounding Shape, for an Object, Generated Using Edge-depth Values for the Object
GOOGLE LLC
0 cites - US121387932024Machine Learning Methods and Apparatus for Robotic Manipulation and That Utilize Multi-task Domain Adaptation
GOOGLE LLC
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- US121124942024Robotic Manipulation Using Domain-invariant 3D Representations Predicted from 2.5D Vision Data
GOOGLE LLC
0 cites - US120793082024Mitigating Reality Gap Through Modification of Simulated State Data of Robotic Simulator
GOOGLE LLC
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- US118873632024Training a Deep Neural Network Model to Generate Rich Object-centric Embeddings of Robotic Vision Data
GOOGLE LLC
0 cites - US118398752023Driving Circuit, Method for Driving the Same, and Microfluidic Device
Shanghai Tianma Micro-electronics Co., Ltd.
0 cites - US118336612023Utilizing Past Contact Physics in Robotic Manipulation (e.g., Pushing) of an Object
GOOGLE LLC
0 cites - US118230482023Generating Simulated Training Examples for Training of Machine Learning Model Used for Robot Control
GOOGLE LLC
0 cites - US117900422023Mitigating Reality Gap Through Modification of Simulated State Data of Robotic Simulator
GOOGLE LLC
0 cites - US117722722023System(s) and Method(s) of Using Imitation Learning in Training and Refining Robotic Control Policies
GOOGLE LLC
0 cites - US117078402023Mitigating Reality Gap Through Optimization of Simulated Hardware Parameter(s) of Simulated Robot
GOOGLE LLC
0 cites - US116575272023Robotic Control Based on 3D Bounding Shape, for an Object, Generated Using Edge-depth Values for the Object
X DEVELOPMENT LLC
0 cites - US115544832023Robotic Grasping Prediction Using Neural Networks and Geometry Aware Object Representation
GOOGLE LLC
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