The paper addresses object localization via a distributed sensor network. A centralized estimation approach is undertaken along with a selective node activation strategy to ensure...
Near regular textures are pervasive in man-made and natural world. Their global regularity and local randomness pose new difficulties to the state of the art texture analysis and ...
Wen-Chieh Lin, James Hays, Chenyu Wu, Yanxi Liu, V...
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...
This work proposes the use of an adaptive neighborhood procedure to extract local statistical properties of images in order to improve a speckle noise "Maximum a Posteriori &q...
We address the problem of minimum distance localization in environments that may contain self-similarities. A mobile robot is placed at an unknown location inside a ¢¤£ self-sim...