added a few MLPerf examples

docs/mlperf-automation/README.md

@@ -5,6 +5,13 @@ using the ACM methodology and automated workflows to reproduce results from rese
 ([ACM TechTalk intro](https://youtu.be/7zpeIVwICa4) and [Artifact Evaluation](https://cTuning.org/ae)) 
 and open-source tools from the MLCommons™ Best Practices WorkGroup ([MLCube™](https://github.com/mlcommons/mlcube)).
 
+A few examples: 
+* [MLPerf™ object detection workflow](https://github.com/ctuning/ck/blob/master/docs/mlperf-automation/tasks/task-object-detection.md)
+* [Docker image for MLPerf™ with OpenVINO](https://github.com/ctuning/ck-ml/tree/main/docker/mlperf-inference-v0.7.openvino)
+* [Jupyter notebook for ML DSE](https://nbviewer.jupyter.org/urls/dl.dropbox.com/s/f28u9epifr0nn09/ck-dse-demo-object-detection.ipynb)
+* [Webcam test of the MLPerf object detection model with TFLite](https://cknowledge.io/solution/demo-obj-detection-coco-tf-cpu-webcam-linux-azure#test)
+* [Public scoreboard with MLPerf DSE](https://cknowledge.io/result/crowd-benchmarking-mlperf-inference-classification-mobilenets-all)
+
 Feel free to contribute to this collaborative doc by sending your PR [here]( https://github.com/ctuning/ck/pulls )
 or creating tickets at [github.com/mlcommons/inference](https://github.com/mlcommons/inference) and [github.com/ctuning/ck](https://github.com/ctuning/ck).
 Thank you!