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Implementation of "Use of Deep Learning for Characterization of Microfluidic Soft Sensors" (RA-L and ICRA'2018)

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deep-characterization-soft-sensor

This is code for the paper:
Use of Deep Learning for Characterization of Microfluidic Soft Sensors, Seunghyun Han, Taekyoung Kim, Dooyoung Kim, Yong-Lae Park and, Sungho Jo, IEEE Robotics and Automation Letter (RA-L), also selected by ICRA'2018

We implemented this code, under the following packages:

  • Python 3.5.4
  • Tensorflow
  • Numpy

How to train

python main.py --epoch 100

How to test

After training, it saves checkpoint in the ./ckpt folder. You can retrieve checkpoints by setting --test flag 'True'.

python main.py --epoch 100 --test True

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Implementation of "Use of Deep Learning for Characterization of Microfluidic Soft Sensors" (RA-L and ICRA'2018)

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