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- W4362474829 abstract "In this study, we proposed smart finger devices (SFDs) for an object classification system using unimodal temperature sensors. Each SFD comprised a module with a flexible thermoelectric device (TED) and a resistance temperature detector (RTD) sensor embedded in a silicone finger cot mounted on a robot gripper. The stored Peltier heat on the TED of the SFD was transferred to the object when the robot gripper grasped it. The RTD sensor data obtained through a one-dimensional convolutional neural network (1D-CNN) distinguished materials with similar thermal conductivities. Through two preprocessing steps, the sensor data were fed into the designed classifier to identify ten selected objects. Finally, our configured classifier performed real-time recognition using unimodal temperature sensors." @default.
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- W4362474829 date "2023-06-01" @default.
- W4362474829 modified "2023-10-03" @default.
- W4362474829 title "Object classification system using temperature variation of smart finger device via machine learning" @default.
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- W4362474829 doi "https://doi.org/10.1016/j.sna.2023.114338" @default.
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