Convolutional Network for Tool Discrimination

نویسندگان

  • Robinson Jiménez
  • Oscar Avilés
چکیده

The present paper discusses the use of deep learning techniques, in particular a convolutional neural network, which is trained to identify, in an image, a surgical cutting tool located on a plane. Initially a database is established regarding the tool with different rotations and after this, the base structure of the convolutional network for its training is determined. It is possible to obtain an average identification percentage of 89% with respect to its discrimination in a group of tools also of surgical cut.

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تاریخ انتشار 2017