stands for Digital Object Identifier
and is the unique identifier for objects on the internet. It can be used to create persistent link and to cite articles.
Using DOI as a persistent link
To create a persistent link, add「http://dx.doi.org/」
before a DOI.
For instance, if the DOI of an article is 10.5297/ser.1201.002 , you can link persistently to the article by entering the following link in your browser: http://dx.doi.org/ 10.5297/ser.1201.002 。
The DOI link will always direct you to the most updated article page no matter how the publisher changes the document's position, avoiding errors when engaging in important research.
Cite a document with DOI
When citing references, you should also cite the DOI if the article has one. If your citation guideline does not include DOIs, you may cite the DOI link.
DOIs allow accurate citations, improve academic contents connections, and allow users to gain better experience across different platforms. Currently, there are more than 70 million DOIs registered for academic contents. If you want to understand more about DOI, please visit airiti DOI Registration （ doi.airiti.com ） 。
-  Omar Javed, Sohaib Khan, Zeeshan Rasheed, and Mubarak Shah, “Camera Handoff: Tracking in Multiple Uncalibrated Stationary Cameras,” IEEE Workshop on Human Motion, pp.113-118, 2000.
-  Sohaib Khan and Mubarak Shah, “Consistent Labeling of Tracked Objects in Multiple Cameras with Overlapping Fields of View,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 25, no. 25, pp.1355-1360, 2003.
-  Arslan Basharat, Alexei Gritai, and Mubarak Shah, “Learning Object Motion Patterns for Anomaly Detection and Improved Object Detection,” IEEE Conf. of Computer Vision and Pattern Recognition (CVPR), 2008.
-  Mubarak Shah, Asaad Hakeem, and Arslan Basharat, “Detection and Tracking of Objects from Multiple Airborne Cameras,” Publication of SPIE, March 2006.
-  Yaser Sheikh, Xin Li, and Mubarak Shah, “Trajectory Association across Non-overlapping Moving Cameras in Planar Scenes,” IEEE Conf. of Computer Vision and Pattern Recognition (CVPR), pp.1-7, 2007.
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