In this paper, we propose a novel predictive model for
object boundary, which can integrate information from any
sources. The model is a dynamic “object” model whose
manifes...
Tian Shen (Lehigh University), Hongsheng Li (Lehig...
We present a new class of deformable models, MetaMorphs, whose formulation integrates both shape and interior texture. The model deformations are derived from both boundary and re...
We discover communities from social network data, and analyze the community evolution. These communities are inherent characteristics of human interaction in online social network...
Yu-Ru Lin, Yun Chi, Shenghuo Zhu, Hari Sundaram, B...
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
In this paper, we present a Gaussian mixture model based approach to capture the spatial characteristics of any target signal in a sensor network, and further propose a temporally...