CVer Learns ML.

I am Shicai, interested in Computer Vision, Pattern Recognition, Machine Learning and Web Design. @Southeast University, Nanjing 211189, PR China

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CVPR (Computer Vision)(Average MAP score: 0.19)

CVPR (Computer Vision) 2012

( MAP score: 0.0 )

CVPR (Computer Vision) 2011

( MAP score: 1.0 )

CVPR (Computer Vision) 2010

( MAP score: 0.0 )

CVPR (Computer Vision) 2009

( MAP score: 0.0 )

CVPR (Computer Vision) 2008

( MAP score: 0.0 )

CVPR (Computer Vision) 2007

( MAP score: 0.0 )

CVPR (Computer Vision) 2006

( MAP score: 0.0 )

CVPR (Computer Vision) 2005

( MAP score: 0.0 )

CVPR (Computer Vision) 2004

( MAP score: 0.0 )

CVPR (Computer Vision) 2003

( MAP score: 0.28 )

CVPR (Computer Vision) 2001

( MAP score: 0.0 )

CVPR (Computer Vision) 2000

( MAP score: 1.0 )

 

MAP (Mean Average Precision) is a measure to evaluate the ranking performance. The MAP score of a conference in a year is calculated by viewing best papers of the conference in the corresponding year as the ground truth and the top cited papers as the ranking results.

MAP(conference, year) = 1/3 \times \sum_{n=1,...,3} \frac{#best_paper_in_top_n_cited_papers}{n}

 

From:http://arnetminer.org

posted on 2013-04-09 16:10  Shicai Yang  阅读(1283)  评论(1编辑  收藏  举报