• DOI:10.1109/PRIME.2019.8787748
Corpus ID: 199489461

DCNN for Tactile Sensory Data Classification based on Transfer Learning

@article{Alameh2019DCNNFT,
  title={DCNN for Tactile Sensory Data Classification based on Transfer Learning},
  author={M. Alameh and Ali Ibrahim and M. Valle and Gabriele Moser},
  journal={2019 15th Conference on Ph.D Research in Microelectronics and Electronics (PRIME)},
  year={2019},
  pages={237-240}
}

• M. Alameh, Ali Ibrahim, +1 author Gabriele Moser
• Published 2019
• Computer Science
• 2019 15th Conference on Ph.D Research in Microelectronics and Electronics (PRIME)

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… Expand

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