diff --git a/README.md b/README.md
index d04d52f..7fc1848 100644
--- a/README.md
+++ b/README.md
@@ -139,3 +139,36 @@ Example:
cd build
./map_demo dla34_cnet.rt c ../demo/COCO_val2017/all_labels.txt ../demo/config.yaml
```
+
+## Supported networks
+
+| Test Name | Network | Dataset | N Classes | Input size | Weights |
+| :---------------- | :-------------------------------------------- | :-----------------------------------------------------------: | :-------: | :-----------: | :------------------------------------------------------------------------ |
+| yolo | YOLO v21 | [COCO 2014](http://cocodataset.org/) | 80 | 608x608 | weights |
+| yolo_224 | YOLO v21 | [COCO 2014](http://cocodataset.org/) | 80 | 224x224 | weights |
+| yolo_berkeley | YOLO v21 | [BDD100K ](https://bair.berkeley.edu/blog/2018/05/30/bdd/) | 10 | 416x736 | weights |
+| yolo_relu | YOLO v2 (with ReLU, not Leaky)1 | [COCO 2014](http://cocodataset.org/) | 80 | 416x416 | weights |
+| yolo_tiny | YOLO v2 tiny1 | [COCO 2014](http://cocodataset.org/) | 80 | 416x416 | weights |
+| yolo_voc | YOLO v21 | [VOC ](http://host.robots.ox.ac.uk/pascal/VOC/) | 21 | 416x416 | weights |
+| yolo3 | YOLO v32 | [COCO 2014](http://cocodataset.org/) | 80 | 416x416 | [weights](https://cloud.hipert.unimore.it/s/jPXmHyptpLoNdNR/download) |
+| yolo3_berkeley | YOLO v32 | [BDD100K ](https://bair.berkeley.edu/blog/2018/05/30/bdd/) | 10 | 320x544 | weights |
+| yolo3_coco4 | YOLO v32 | [COCO 2014](http://cocodataset.org/) | 4 | 416x416 | weights |
+| yolo3_flir | YOLO v32 | [FREE FLIR](https://www.flir.com/oem/adas/adas-dataset-form/) | 3 | 320x544 | weights |
+| yolo3_tiny | YOLO v3 tiny2 | [COCO 2014](http://cocodataset.org/) | 80 | 416x416 | [weights](https://cloud.hipert.unimore.it/s/LMcSHtWaLeps8yN/download) |
+| yolo3_tiny512 | YOLO v3 tiny2 | [COCO 2017](http://cocodataset.org/) | 80 | 512x512 | [weights](https://cloud.hipert.unimore.it/s/pjooA5DMrrEbrmA/download) |
+| dla34 | Deep Leayer Aggreagtion (DLA) 343 | [COCO 2014](http://cocodataset.org/) | 80 | 224x224 | weights |
+| dla34_cnet | Centernet (DLA34 backend)4 | [COCO 2017](http://cocodataset.org/) | 80 | 512x512 | [weights](https://cloud.hipert.unimore.it/s/8AjXdgCeRzCa5AF/download) |
+| mobilenetv2ssd | Mobilnet v2 SSD Lite5 | [VOC ](http://host.robots.ox.ac.uk/pascal/VOC/) | 21 | 300x300 | [weights](https://cloud.hipert.unimore.it/s/x4ZfxBKN23zAJQp/download) |
+| resnet101 | Resnet 1016 | [COCO 2014](http://cocodataset.org/) | 80 | 224x224 | weights |
+| resnet101_cnet | Centernet (Resnet101 backend)4 | [COCO 2017](http://cocodataset.org/) | 80 | 512x512 | [weights](https://cloud.hipert.unimore.it/s/B6mj33k7beECXsY/download) |
+
+
+
+## References
+
+1. Redmon, Joseph, and Ali Farhadi. "YOLO9000: better, faster, stronger." Proceedings of the IEEE conference on computer vision and pattern recognition. 2017.
+2. Redmon, Joseph, and Ali Farhadi. "Yolov3: An incremental improvement." arXiv preprint arXiv:1804.02767 (2018).
+3. Yu, Fisher, et al. "Deep layer aggregation." Proceedings of the IEEE conference on computer vision and pattern recognition. 2018.
+4. Zhou, Xingyi, Dequan Wang, and Philipp Krähenbühl. "Objects as points." arXiv preprint arXiv:1904.07850 (2019).
+5. Sandler, Mark, et al. "Mobilenetv2: Inverted residuals and linear bottlenecks." Proceedings of the IEEE conference on computer vision and pattern recognition. 2018.
+6. He, Kaiming, et al. "Deep residual learning for image recognition." Proceedings of the IEEE conference on computer vision and pattern recognition. 2016.
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