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MBRM[1] 0.24/0.25/0.245/122 0.18/0.19/0.185/209 0.24/0.23/0.235/233 JEC[3] 0.27/0.32/0.293/139 0.22/0.25/0.234/224 0.28/0.29/0.285/250 TagProp-ML[2] 0.31/0.37/0.337/146 0.49/0.20/0.284/213 0.48/0.25/0.329/227 TagProp-s ML[2] 0.33/0.42/0.370/160 0.39/0.27/0.319/239 0.46/0.35/0.398/266 KSVM 0.29/0.43/0.346/174 0.30/0.28/0.290/256 0.43/0.27/0.332/266 KSVM-VT (Ours) 0.32/0.42/0.363/179 0.33/0.32/0.325/259 0.47/0.29/0.359/268 Table 1: Performance comparison among different methods. The prefix ‘K’ corresponds to kernelization using chi-squared kernel.

Exploring SVM for Image Annotation in Presence of Confusing Labels