9, IO]. However, unlike the case with static timing, it is not so easy We show how recent advances in the handling of correlated interval representations of range uncertainty can b...
Domain adaptation solves a learning problem in a target domain by utilizing the training data in a different but related source domain. Intuitively, discovering a good feature rep...
Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, Qi...
Abstract. We present two data-driven importance distributions for particle filterbased articulated tracking; one based on background subtraction, another on depth information. In ...
Linear Discriminant Analysis (LDA) has been a popular method for feature extracting and face recognition. As a supervised method, it requires manually labeled samples for training...
Information seeking is traditionally conducted in environments where search results are represented at the user interface by a minimal amount of meta-information such as titles an...