We present a method to learn visual attributes (eg.“red”,
“metal”, “spotted”) and object classes (eg. “car”,
“dress”, “umbrella”) together. We assume imag...
Recently, nonlinear shape models have been shown to improve the robustness and flexibility of segmentation. In this paper, we propose Shape Regularized Active Contour (ShRAC) that...
In this paper, we propose a machine learning approach to title extraction from general documents. By general documents, we mean documents that can belong to any one of a number of...
Yunhua Hu, Hang Li, Yunbo Cao, Dmitriy Meyerzon, Q...
This paper aims to investigate the use of mobile agents for service provision in mobile computing environments. A quantitative model and experimental measurements are performed to ...
Ouahiba Fouial, Nadia Boukhatem, Isabelle M. Demeu...
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...