diff --git a/docs/source/main/model_zoo/MODEL_ZOO.md b/docs/source/main/model_zoo/MODEL_ZOO.md
index 3062312..74c7df0 100644
--- a/docs/source/main/model_zoo/MODEL_ZOO.md
+++ b/docs/source/main/model_zoo/MODEL_ZOO.md
@@ -18,6 +18,7 @@ The [Model ZOO](https://chmura.put.poznan.pl/s/2pJk4izRurzQwu3) is a collection
 | [Fire risk assesment](https://chmura.put.poznan.pl/s/NxKLdfdr9s9jsVA)                | 384        | 100   | Trained on the FireRisk dataset (RGB data). Classifies risk of fires (ver_high, high, low, ...). Uses ConvNeXt XXL. Val F1-score 	65.5.                                                                                                                                                                                                                                                                                                                                                                      | [Image](https://chmura.put.poznan.pl/s/Ijn3VgG76NvYtDY) |
 | [Roads Segmentation](https://chmura.put.poznan.pl/s/y6S3CmodPy1fYYz)                 | 512        | 21    | The model segments the Google Earth satellite images into 'road' and 'not-road' classes. Model works best on wide car roads, crossroads and roundabouts.                                                                                                                                                                                                                                                                                                                                                     | [Image](https://chmura.put.poznan.pl/s/rln6mpbjpsXWpKg) |
 | [Solar PV Segmentation](https://owncloud.fraunhofer.de/index.php/s/Ph9TC6BTxPi5oZZ)                 | 512        | 20    | Model trained by M Kleebauer et al. in "[Multi-resolution segmentation of solar photovoltaic systems using deep learning](https://www.mdpi.com/2596164) on a diverse range of image data, spanning UAV, aerial, and satellite imagery at both native and aggregated resolutions of 0.1 m, 0.2 m, 0.3 m, 0.8 m, 1.6 m, and 3.2 m.                                                                                                                                                                                                                                                                                                                                                      | [Image](https://github.com/Kleebaue/multi-resolution-pv-system-segmentation/blob/main/figures/prediction_multi_res.png) |
+| [Noise Insulating Walls Segmentation](https://github.com/merantix-momentum/dzsf-open-source/releases/download/v0.0.1/model.zip)                 | 1000        | 20    | Model trained by [Merantix Momentum](https://merantix-momentum.github.io/dzsf-open-source/) on Digital Orthophotos of the whole Germany to detect noise insulating walls near train railways.   | [Image](https://github.com/merantix-momentum/dzsf-open-source/blob/main/assets/images/prediction_1.png)
 
 ## Regression models