We propose methods for outlier handling and noise reduction using weighted local linear smoothing for a set of noisy points sampled from a nonlinear manifold. The methods can be u...
Jin Hyeong Park, Zhenyue Zhang, Hongyuan Zha, Rang...
We present a method for training a similarity metric from data. The method can be used for recognition or verification applications where the number of categories is very large an...
It was prescriptive that an image matrix was transformed into a vector before the kernel-based subspace learning. In this paper, we take the Kernel Discriminant Analysis (KDA) alg...
Shuicheng Yan, Dong Xu, Lei Zhang, Benyu Zhang, Ho...
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
Object detection can be posted as those classification tasks where the rare positive patterns are to be distinguished from the enormous negative patterns. To avoid the danger of m...