We present a method for automatically learning discriminative image patches for the recognition of given object classes. The approach applies discriminative training of log-linear...
Our research extends the general technologies detecting pornographic images to prevent the benign images whose content is approximate with the pornographic ones from being screene...
In this work we present a novel approach for learning nonhomogenous textures without facing the unlearning problem. Our learning method mimics the human behavior of selective lear...
It has been shown that features can be selected adaptively for object tracking in changing environments [1]. We propose to use the variance of Mutual Information [2] for online fea...
In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...