Studies from Chinese Academy of Sciences Provide New Data on Knowledge-based Systems

摘要

2011 APR 4 - (VerticalNews.com) -- "Semi-supervised dimensional reductionrnmethods play an important role in pattern recognition, which are likely to be more suitable forrnplant leaf and palmprint classification, since labeling plant leaf and palmprint often requiresrnexpensive human labor, whereas unlabeled plant leaf and palmprint is far easier to obtain at veryrnlow cost. In this paper, we attempt to utilize the unlabeled data to aid plant leaf and palmprintrnclassification task with the limited number of the labeled plant leaf or palmprint data, andrnpropose a semi-supervised locally discriminant projection (SSLDP) algorithm for plant leaf andrnpalmprint classification," investigators in Anhui, People's Republic of China report.