paper chnages (#63)

paper/paper.bib

@@ -117,4 +117,5 @@ @misc{rastervision
   url="https://github.com/azavea/raster-vision",
   author="Fishgold, Lewis and Hassan, Adeel and Emanuele, Rob and McClain, James and Kassel, Simon and Zhao, Annie and {jpolchlo} and Morrison, Joe and Bakker, Laurens and Santucci, James and Holeman, Nathan and {rbreslow} and {Taylor} and Park, Bborie and Liedman, Per and Kalra, Umang and Sani, Ammar and Meier, Andreas and Brown, Chris and McCallum, Chuck and Kettler, Cole and Cheipesh, Eugene and {Grigory} and Maleski, Jerome and Bertrand, Matt and Uryu, Shinya",
   doi="10.5281/zenodo.8018177",
+  year=2023,
 }

paper/paper.jats

@@ -136,8 +136,8 @@ a Creative Commons Attribution 4.0 International License (CC BY
   <p>Several unified libraries like torchgeo
   (<xref alt="Stewart et al., 2022" rid="ref-Stewart_TorchGeo_Deep_Learning_2022" ref-type="bibr">Stewart
   et al., 2022</xref>) and rastervision
-  (<xref alt="Fishgold et al., n.d." rid="ref-rastervision" ref-type="bibr">Fishgold
-  et al., n.d.</xref>) exists, but they are primarily targeted for
+  (<xref alt="Fishgold et al., 2023" rid="ref-rastervision" ref-type="bibr">Fishgold
+  et al., 2023</xref>) exists, but they are primarily targeted for
   PyTorch user community. Some efforts for GEE &amp; TensorFlow users,
   such as geemap
   (<xref alt="Wu, 2020" rid="ref-Wu2020" ref-type="bibr">Wu,
@@ -467,6 +467,7 @@ a Creative Commons Attribution 4.0 International License (CC BY
         <name><surname>Uryu</surname><given-names>Shinya</given-names></name>
       </person-group>
       <article-title>Raster Vision: An open source library and framework for deep learning on satellite and aerial imagery (2017-2023)</article-title>
+      <year iso-8601-date="2023">2023</year>
       <uri>https://github.com/azavea/raster-vision</uri>
       <pub-id pub-id-type="doi">10.5281/zenodo.8018177</pub-id>
     </element-citation>