Update README file

Add information about the research project and the fund.

README.md

@@ -4,10 +4,49 @@ emoji: 🏃
 colorFrom: indigo
 colorTo: blue
 sdk: gradio
-sdk_version: 5.38.2
+sdk_version: 5.39.0
 app_file: app.py
 pinned: false
+license: cc-by-4.0
 short_description: Rebar detection models published in IWAGPR25
 ---
+## 📜 Paper Citation
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+This Space is based on the research presented in our paper. If you use this work, please cite the following publication:
+
+```bibtex
+@inproceedings{elseicy2025rebar,
+	title        = {Preliminary Study on Automating Rebar Detection in Reinforced Concrete Structures Using YOLOv11 and GPR Data},
+	author       = {Elseicy, Ahmed and Solla, Mercedes and Novo, Alexandre},
+	year         = 2025,
+	month        = {July},
+	booktitle    = {2025 13th International Workshop on Advanced Ground Penetrating Radar (IWAGPR)},
+	publisher    = {IEEE},
+	pages        = {323--328},
+	isbn         = {979-8-3315-2335-0},
+	issn         = {2687-7899}
+}
+
+```
+## 💾 Dataset Reference
+
+The full models and the dataset used in the project are published in Zenodo.
+```bibtex
+@misc{elseicy_2025_16638791,
+	title        = {Deep learning model for rebar detection from GPR data},
+	author       = {Elseicy, Ahmed and Solla, Mercedes},
+	year         = 2025,
+	month        = jul,
+	publisher    = {Zenodo},
+	doi          = {10.5281/zenodo.16638791},
+	url          = {https://doi.org/10.5281/zenodo.16638791}
+}
+```
+## 💰 Funding Acknowledgement
+
+This research and development were made possible through the OVERSIGHT project (PID2022-138526OB-I00) funded by MICIU/AEI/10.13039/501100011033/FEDER, UE.
+Grant PREP2022-000030 for the training of predoctoral researchers funded by MICIU/
+AEI/10.13039/501100011033 and by FSE+. 
+M. Solla acknowledges the Grant RYC2019–026604–I funded by MICIU/
+AEI/10.13039/501100011033 and by “ESF Investing in
+your future”.