DCNN for Tactile Sensory Data Classification based on Transfer Learning
@article{Alameh2019DCNNFT, title={DCNN for Tactile Sensory Data Classification based on Transfer Learning}, author={Mohamad Gabriel Alameh and Ali Ibrahim and Maurizio Valle and Gabriele Moser}, journal={2019 15th Conference on Ph.D Research in Microelectronics and Electronics (PRIME)}, year={2019}, pages={237-240} }
Tactile data processing and analysis is still essentially an open challenge. In this framework, we demonstrate a method to achieve touch modality classification using pre-trained convolutional neural networks (CNNs). The 3D tensorial tactile data generated by real human interactions on an electronic skin (E-Skin) are transformed into 2D images. Using a transfer learning approach formalized through a CNN, we address the challenging task of the recognition of the object that was touched by the E…
7 Citations
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