most citedSegmentation of Surgical Instruments for Minimally-Invasive Robot-Assisted Procedures Using Generative Deep Neural Networks

4 citations · 4 across the 1 of their papers we have counts for

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1 paper

cs.CV2020★ 4 cited

Segmentation of Surgical Instruments for Minimally-Invasive Robot-Assisted Procedures Using Generative Deep Neural Networks

Iñigo Azqueta-Gavaldon, Florian Fröhlich, Klaus Strobl +1

This work proves that semantic segmentation on minimally invasive surgical instruments can be improved by using training data that has been augmented through domain adaptation. The…