Update README.md

README.md

@@ -9,15 +9,57 @@ tags:
 - effect of background
 - background correlations
 - synthetic
+- synset
 - OCTAS
 pretty_name: Synset Background Effect Datasets
 ---
 
+<img src="synset-background-effect-datasets-title-image.png" width=100% />
+
 # Synset Background Effect Datasets
 
 <!-- Provide a quick summary of the dataset. -->
+For investigating the effect of background on feature importance and classification performance, we systematically generated six synthetic datasets for the 
+task of traffic sign recognition, which differ only in their degree of camera variation and background correlation. Each of these datasets contains 82 classes 
+of traffic signs with 1,100 images per class, resulting in 90,200 images per dataset, summing up to a total of 541,200 images.
+
+**Website**: [synset.de/datasets/synset-signset-ger/background-effect/](https://synset.de/datasets/synset-signset-ger/background-effect/) <br>
+**Paper:** Sielemann, A., Barner, V., Wolf, S., Roschani, M., Ziehn, J. and Beyerer, J. (2025). [Measuring the Effect of Background on Classification and Feature Importance in Deep Learning for AV Perception](https://ieeexplore.ieee.org/abstract/document/11219547). In 2025 IEEE International Automated Vehicle Validation Conference (IAVVC). [[arXiv](https://arxiv.org/abs/2512.05937)]  <br>
+**Authors:** [Anne Sielemann](https://www.linkedin.com/in/anne-sielemann-23011026a/), Valentin Barner, [Stefan Wolf](https://www.linkedin.com/in/stefan-wolf-2552211a9/),
+Masoud Roschani, [Jens Ziehn](https://www.linkedin.com/in/jrziehn/), and Juergen Beyerer. [Fraunhofer IOSB](https://www.iosb.fraunhofer.de/), Germany.  <br>
+**Funded by:** [Fraunhofer](https://www.fraunhofer.de/en.html) Internal Programs under Grant No. PREPARE 40-02702 within the ML4Safety project and the [German Federal Ministry for Economic Affairs and Climate Action](https://www.bundeswirtschaftsministerium.de/Navigation/EN/Home/home.html), within the program “New Vehicle and System Technologies” as part of the [AVEAS](https://aveas.org/) research project. <br>
+**License:** CC-BY 4.0 <br>
+
+## Citation
+
+<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+    @inproceedings{measuring_effect_of_background_sielemann_2025,
+      title={{Measuring the Effect of Background on Classification and Feature Importance in Deep Learning for AV Perception}},
+      author={Sielemann, Anne and Barner, Valentin and Wolf, Stefan and Roschani, Masoud and Ziehn, Jens and Beyerer, Juergen},
+      booktitle={2025 IEEE International Automated Vehicle Validation Conference (IAVVC)},
+      year={2025}
+    }
+
+
+**APA:**
+
+Sielemann, A., Barner, V., Wolf, S., Roschani, M., Ziehn, J., and Beyerer, J. (2025). <br>
+Measuring the Effect of Background on Classification and Feature Importance in Deep Learning for AV Perception. <br>
+In 2025 IEEE International Automated Vehicle Validation Conference (IAVVC).
+
+## Bias, Risks, and Limitations
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+<!-- Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. -->
 
-**Download / more info**: [synset.de/datasets/synset-signset-ger/background-effect/](https://synset.de/datasets/synset-signset-ger/background-effect/)
+It is recommended to use the dataset primarily for scientific research. Application to practical real-world use cases should include
+human oversight and the exhaustive evaluation of the fitness for the respective purpose, including the impact of domain shifts.
 
 ## Dataset Card Contact