Update README.md

README.md

@@ -7,7 +7,6 @@ The implementation of the presented methodology consists of several tools:
 - Within the FME workspace coregistration.fmw Python 3.7 scripts and libraries [Open3D](http://www.open3d.org/) and [Pyntcloud](https://github.com/daavoo/pyntcloud) are integrated
 - The inference of the Bayesian network is performed in [R](https://www.r-project.org/) using the [bnspatial](https://cran.r-project.org/web/packages/bnspatial/bnspatial.pdf) package.
 - The network can is designed in [GeNIe](https://download.bayesfusion.com/files.html?category=Academia) but one can use similar software (see [Stritih et al., 2020](https://www.sciencedirect.com/science/article/pii/S1364815219306061) for a nice overview)
-- The workflow is designed to digest MLS point clouds and a CityGML building (so to say N:1). The output is a probability map in the .png format
 
 <p float="center">
     <img src="images/UnderpassJourImplementation.png" width="100%" title="implementation overview"/>