Multiresolution pyramid techniques can improve the efficiency of basic vision algorithms by orders of magnitude. They will be key to developing practical vision systems to perform challenging tasks in real time. However, these efficiencies cannot be fully realized when pyramid-based algorithms are implemented on machines with conventional SIMD mesh and pipeline architectures. We describe a segm...

In their book, Granular Computing: An Introduction, Bargiela and Pedrycz present a view that granular computing is an emerging conceptual and computing paradigm of information processing. A central notion is an information-processing pyramid with multiple levels. Different levels involve different types of processing. The lowest level concerns numeric processing, the intermediate level concerns...

This paper represents Hybrid model image fusion algorithm based on combination of pyramid method and Wavelet method .To improve the Quality of output image an Algorithm is proposed by using Laplacian pyramid and Gradient pyramid methods from pyramid method and, Haar wavelet from Wavelet method. This algorithm creates new images for further image processing applications like Enhancement, Segment...

Pyramid networks have long been proposed for parallel processing. However, when the network contains multiple pairs of source and destination nodes, it is often difficult to use the pyramid efficiently since most of the algorithms try to simultaneously use the apex for each pair of nodes. Therefore, there may exist a severe bottleneck in such circumstances. We propose a Least Level Minimal Rout...

We present results from using a version of the pyramid method to create gold standards for evaluation of automatic text summarization techniques in the domain of governmental texts. Our results show that the pyramid method may be useful to create gold standards for extraction based summarization techniques using only five human summarisers.

The pyramid evaluation effort for the 2006 Document Understanding Conference involved twenty-two sites on twenty document sets. Each pyramid content model (one per document set) was constructed from four human summaries. Peer systems were scored using the modified pyramid score introduced in DUC 2005. ANOVAs with score as the independent variable and nine factors yielded three significant facto...

The contemporary information technologies and Internet impose high requirements on the image compression efficiency. Great number of methods for information redundancy reduction had already been developed, which are based on the image processing in the spatial or spectrum domain. Other methods for image compression use some kinds of neural networks. In spite of their potentialities, the methods...

In this paper, we share our experience in designing a convolutional network-based face detector that could handle faces of an extremely wide range of scales. We show that faces with different scales can be modeled through a specialized set of deep convolutional networks with different structures. These detectors can be seamlessly integrated into a single unified network that can be trained end-...

| We present Gibbs Markov random eld models as a powerful and robust descriptor of spatial information in typical remote sensing image data. This class of stochastic image models provides an intuitive description of the image data using parameters of an energy function. For the selection among several nested models and the t of the model we proceed in two steps of Bayesian inference. This proce...

We present Gibbs–Markov random field (GMRF) models as a powerful and robust descriptor of spatial information in typical remote-sensing image data. This class of stochastic image models provides an intuitive description of the image data using parameters of an energy function. For the selection among several nested models and the fit of the model, we proceed in two steps of Bayesian inference. ...