Principal Component Analysis (PCA) is a basis transformation to diagonalize an estimate of the covariance matrix of input data and, the new coordinates in the Eigenvector basis ar...
Following the phenomenological approach of gestaltists, sparse monocular depth cues such as T- and X-junctions and the local convexity are crucial to identify the shape and depth ...
Background: The hierarchical and partially redundant nature of protein structures justifies the definition of frequently occurring conformations of short fragments as `states'...
Different modalities in biomedical imaging, like CT, MRI and PET scanners, provide detailed crosssectional views of the human anatomy. The imagery obtained from these scanning dev...
Localization is an important and extensively studied problem in ad-hoc wireless sensor networks. Given the connectivity graph of the sensor nodes, along with additional local info...
Amitabh Basu, Jie Gao, Joseph S. B. Mitchell, Giri...