We present a new approach to detecting defects in random textures which requires only very few defect free samples for unsupervised training. Each product image is divided into ove...
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
In this paper, we present a mixture Principal Component Analysis (mPCA)-based approach for voxel level quantification of dynamic positron emission tomography (PET) data in brain s...
Intra-personal space modeling proposed by Moghaddam et. al. has been successfully applied in face recognition. In their work the regular principal subspaces are derived from the i...
Shaohua Kevin Zhou, Rama Chellappa, Baback Moghadd...
This paper presents a real-time single-camera surveillance system, aiming at detecting and partly analyzing a group of people. A set of moving persons is segmented using a combina...