Update README.md

Author: vancha-MW

README.md

@@ -20,7 +20,7 @@ This repository implements two variants of the complex YOLO v4 object detectors:
 - **complex-yolov4-pandaset**: Standard complex yolov4 network for accurate object detection.
 - **tiny-complex-yolov4-pandaset**: Lightweight complex yolov4 network for faster inference.
 
-The pretrained networks are trained on three different object categories Car, Truck and Pedestrain. These networks are trained using Pandaset dataset[3].
+The pretrained networks are trained on three different object categories Car, Truck and Pedestrain. These networks are trained on the Pandaset dataset, available at https://scale.com/open-datasets/pandaset.
 
 For other variant of Lidar object detection network, refer [Lidar 3-D Object Detection Using PointPillars Deep Learning](https://www.mathworks.com/help/lidar/ug/object-detection-using-pointpillars-network.html).
 
@@ -144,6 +144,4 @@ References
 
 [2] Simon, Martin, et al. “Complex-YOLO: Real-Time 3D Object Detection on Point Clouds.” ArXiv:1803.06199 [Cs], Sept. 2018. arXiv.org, http://arxiv.org/abs/1803.06199. 
 
-[3] [Panda Set](https://scale.com/open-datasets/pandaset) is provided by Hesai and Scale under the [CC-BY-4.0 license](https://creativecommons.org/licenses/by/4.0)
-
 Copyright 2021 The MathWorks, Inc.