Mask R-CNN based droplet detection in liquid–liquid systems, Part 2: Methodology for determining training and image processing parameter values improving droplet detection accuracy

Chemical Engineering Journal, vol. 473, pp. 144826

Authors 5

1. Stepan Sibirtsev Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, Fluid Process Engineering (AVT.FVT), Forckenbeckstraße 51, 52074 Aachen, Germany

2. Song Zhai Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, Fluid Process Engineering (AVT.FVT), Forckenbeckstraße 51, 52074 Aachen, Germany

3. Mathias Neufang Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, Fluid Process Engineering (AVT.FVT), Forckenbeckstraße 51, 52074 Aachen, Germany

4. Jakob Seiler Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, Fluid Process Engineering (AVT.FVT), Forckenbeckstraße 51, 52074 Aachen, Germany

5. Andreas Jupke corresponding Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, Fluid Process Engineering (AVT.FVT), Forckenbeckstraße 51, 52074 Aachen, Germany