Update README.md

README.md

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 Towards automated analysis of large environments, hyperspectral sensors must be adapted into a format where they can be operated from mobile robots. In this dataset, we highlight hyperspectral datacubes collected from the [Hyper-Drive ](https://river-lab.github.io/hyper_drive_data/) imaging system. Our system collects and registers datacubes spanning the visible to shortwave infrared (660-1700 nm) in 33 wavelength channels. The system also simultaneously captures the ambient solar spectrum reflected off a white reference tile. The dataset consists of 500 labeled datacubes from on-road and off-road terrain compliant with the [ATLAS](http://gvsets.ndia-mich.org/documents/AAIR/2022/ATLAS,%20an%20All-Terrain%20Labelset%20for%20Autonomous%20Systems.pdf).
 
-This work first appeared at [WHISPERS](https://www.ieee-whispers.com/) 2023 In Athens, Greece and is a product of the  [Robotics and Intelligent Vehicles Research Laboratory (RIVeR)](https://www.robot.neu.edu/) at [Northeastern University](https://www.northeastern.edu/).
+This work first appeared at [WHISPERS](https://www.ieee-whispers.com/) 2023 in Athens, Greece and is a product of the  [Robotics and Intelligent Vehicles Research Laboratory (RIVeR)](https://www.robot.neu.edu/) at [Northeastern University](https://www.northeastern.edu/).
+
+The paper is is available on [Arxiv](https://arxiv.org/abs/2308.08058). If you use our data in your research, please make sure use the following citation:
+
+```
+@inproceedings{hanson2023hyper,
+  title={Hyper-Drive: Visible-Short Wave Infrared Hyperspectral Imaging Datasets for Robots in Unstructured Environments},
+  author={Hanson, Nathaniel and Pyatski, Benjamin and Hibbard, Samuel and DiMarzio, Charles and Pad{\i}r, Ta{\c{s}}k{\i}n},
+  booktitle={2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)},
+  pages={1--5},
+  year={2023},
+  organization={IEEE}
+}
+```
 
 In addition to the 500 labeled hyperspectral datacubes, raw ROS bagfiles generated of each of the sensor feeds at a higher frame rate are available [here](https://river-lab.github.io/hyper_drive_data/Data_Set.html). These files are provided as an additional resource and do not contain semantic labels, but contain ~10,000 additional hyperspectral datacubes of in-between frames from the labeled dataset. It also contains additional datatypes for terrain analysis such as inertial measurement unit (IMU) data. To the best of the authors knowledge, it is the **largest vehicle-centric hyperspectral dataset** currently available!