Sharif Digital Repository

Hand pose estimation is one of the most attractive research areas for image processing. Among the human body parts, hands are particularly important for human–machine interactions. The advent of commercial depth cameras along with the rapid growth of deep learning has made great progress in all image processing fields, especially in hand pose estimation. In this study, using depth data, we introduce two hybrid deep neural networks to estimate 3D hand poses with fewer computations and higher accuracy compared with their counterparts. Due to the fact that the dimensions of data are reduced while passing through successive layers of networks, which causes data to be lost, we use the concept of... 

Three-dimensional (3D) bundles of self-assembled lanthanum hydroxide nanorods with average crystallite size of about 20 nm were fabricated via a facile and rapid microwave-assisted chemical route. The obtained material was characterized with X-ray diffractometry (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) investigations. The obtained nanorods have average diameter of about 115 nm and average length of about 730 nm. Self-assembly of primary La(OH)3 nanoparticles and their subsequent anisotropic growth along 〈2 0 0〉 direction, was proposed to be the mechanism for the formation of 3D bundles of nanorods, using TEM images. The thermal behavior of the... 

Edit distance is one of the most fundamental problems in computer science. Tree edit distance is a natural generalization of edit distance to ordered rooted trees. Such a generalization extends the applications of edit distance to areas such as computational biology, structured data analysis (e.g., XML), image analysis, and compiler optimization. Perhaps the most notable application of tree edit distance is in the analysis of RNA molecules in computational biology where the secondary structure of RNA is typically represented as a rooted tree. The best-known solution for tree edit distance runs in cubic time. Recently, Bringmann et al. show that an O(n2.99) algorithm for weighted tree edit...