For many visual analysis algorithms, these distinct and bright visual features can become a significant source of error.
Furthermore, for many visual analysis algorithms, these distinct and bright visual features can become a significant source of error.
Many network analysis algorithms filter or partition networks based on topological features, optionally weighted by orthogonal node or edge data (Bader and Hogue, 2003; Royer et al., 2008).
This is due to the cost-effectiveness of the Hadoop-based analysis on commodity Linux clusters, and in the cloud via data upload to cloud vendors who have implemented Hadoop/HBase; and due to the effectiveness and ease-of-use of the MapReduce method in parallelization of many data analysis algorithms.
We believe that the proposed scheme can be coupled with many existing content analysis algorithms in sports videos to either speed up or improve the performance.
Many advanced fringe analysis algorithms have been proposed including regularized phase tracking (RPT), partial differential equation based methods, wavelet transform, Wigner Ville distribution, and windowed Fourier transform.
While multi-relational networks are more expressive in terms of the variety of relationships they can capture, there is a need for a general framework for transferring the many single-relational network analysis algorithms to the multi-relational domain.
Many, if not most network analysis algorithms have been designed specifically for single-relational networks; that is, networks in which all edges are of the same type.
High-content screens provide an additional level of complexity, where image analysis algorithms produce many measures reflecting different, but overlapping, aspects of the underlying biology (e.g. spot count, spot intensity and spot area).
In the process the Avian Phylogenomics Group fine-tuned genome assembly, alignment and phylogenetic analysis algorithms, avoiding many artifacts that big-data comparative genomics studies face today and taking the field to a new level.
