Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchial feed-forward models (e.g., convolutional neural networks) showed promise in this direction, they are still difficult to train especially when few training examples are available. In this paper, we present a framework for tra...

The proliferation of epithelial cells lining the small intestinal mucosa may be regulated by microenvironmental signals leading to differentiation of precursor cells in the small intestinal crypts. Proliferation of hematopoietic cells within the hematopoietic microenvironment is known to be regulated by a growing number of glycoprotein growth factors in a hierarchial fashion. We studied the eff...

A low-complexity three-dimensional image compression algorithm based on wavelet transforms and set-partitioning strategy is presented. The Subband Block Hierarchial Partitioning (SBHP) algorithm is modified and extended to three dimensions, and applied to every code block independently. The resultant algorithm, 3D-SBHP, efficiently encodes 3D image data by the exploitation of the dependencies i...

In this paper, we propose a novel practical method for blob-based liquid 3D morphing. Firstly, blobby objects are employed to approximate a given polygonal surface through an energy optimization procedure so that the distance between the isosurface of blobs and the given model is minimized. The primitives in the medial axis sphere-tree of a polygonal model are utilized as initial blobs — this g...

Terms considered as trees are very useful tools for presentation and manipulation of different data structures in Computer Science and Information Technology. Any work of the computer over the trees, for instance as graphical user interface (menus of the different windows), XML documents, definitions and description of hierarchial objects in C++ or Java programming etc. can be considered as run...

Hierarchical clustering is an important technique for hierarchical data exploration applications. However, most existing hierarchial methods are based on traditional one-side clustering, which is not effective for handling high dimensional data. In this paper, we develop a partitional hierarchical co-clustering framework and propose a Hierarchical Information-Theoretical Co-Clustering (HITCC) a...

Deposition of silver onto British 2p coins has been demonstrated as an efficient and cost effective approach to producing substrates capable of promoting surface enhanced Raman scattering (SERS). Silver application to the copper coins is undemanding taking just 20 s, and results in the formation of multiple hierarchial dendritic structures. To demonstrate that the silver deposition sites were c...

This study tested a social learning model and explored the direct and interactive relationships between personality and environment in predicting problem alcohol use. We used longitudinal data from a nonclinical sample of males and females first tested in adolescence and followed into young adulthood. Hierarchial regression analyses were used to test main effects and interaction models. The cro...

Tucker decomposition is the cornerstone of modern machine learning on tensorial data analysis, which have attracted considerable attention for multiway feature extraction, compressive sensing, and tensor completion. The most challenging problem is related to determination of model complexity (i.e., multilinear rank), especially when noise and missing data are present. In addition, existing meth...