Attentive robots, inspired by human-like vision – are required to have visual systems with fovea-periphery distinction and saccadic motion capability. Thus, each frame in the incoming image sequence has nonuniform sa...
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We present a generalized random field model in a random environment to classify hyperspectral textures. The model generalizes traditional random field models by allowing the spatial interaction parameters of the field...
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We present a generalized random field model in a random environment to classify hyperspectral textures. The model generalizes traditional random field models by allowing the spatial interaction parameters of the field to be random variables. Principal component analysis is used to reduce the dimensionality of the data set to a small number of spectral bands that capture almost all of the energy in the original hyperspectral textures. Using the model we obtain a compact feature vector that efficiently computes within and between band information. Using a set of hyperspectral samples, we evaluate the performance of this model for classifying textures and compare the results with other approaches.
We integrate the advantages of SOM- and snake-based ACMs in order to extract the desired contour from images. We employ: (i) the feature points to guide the contour, as in the case of SOM-based ACMs; (ii) the gradient...
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We integrate the advantages of SOM- and snake-based ACMs in order to extract the desired contour from images. We employ: (i) the feature points to guide the contour, as in the case of SOM-based ACMs; (ii) the gradient and intensity variations in a local region to control the contour movement. However, in contrast with the snake-based ACMs, we do not use an explicit energy functional based on gradient or intensity. The algorithm is tested on synthetic binary and gray-level images, and the results show the superiority of the proposed algorithm over other conventional SOM- and snake-based ACM algorithms.
On-Line Analytical Processing (OLAP) is a trend in database technology, based on the multidimensional view of data. Numerous applications and development environments exist, offering OLAP analysis to developers, analy...
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The sensor network for monitoring distributed spatial phenomena has emerged as an area of significant practical interest. In this paper we investigate fundamental issues in detection of spatially distributed phenomena...
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The sensor network for monitoring distributed spatial phenomena has emerged as an area of significant practical interest. In this paper we investigate fundamental issues in detection of spatially distributed phenomena under communication constraints. The novelty of the paper is in providing a tradeoff between global performance and costs involved in communication. In particular we focus our attention on boundary estimation and develop a framework to optimize communication costs subject to worst-case misclassification guarantees. It is shown that the communication cost is primarily a function of two parameters: (1) length of the boundary; (2) overall misclassification error - which leads us to the conclusion that wireless sensor network performance is comparable to that obtained with a wired network of sensors.
The design and development of a 230 W power amplifier operating at S-band (2,35 to 2.45 GHz) is described. The motivation behind this development is the need for a microwave driver amplifier to be used in the linear a...
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The design and development of a 230 W power amplifier operating at S-band (2,35 to 2.45 GHz) is described. The motivation behind this development is the need for a microwave driver amplifier to be used in the linear accelerator facility at the Institute of Accelerating systems and Applications at the University of Athens. It will replace the magnetron currently being used at low microwave power. The need for extremely stable microwave power for the electron beam pre-acceleration and chopping cavities makes it imperative to use a solid-state high power GaAs amplifier. The design technology uses microstrips, fabricated on RO4003 substrates, and special care has been taken to protect the amplifier from over temperature and overload. The amplifier is composed of three stages. The first is a MMIC and the other two use GaAs MESFETs. The amplifier also has forward and reflected signal indicators that can be used for remote amplifier control to shut it down if the VSWR is too high, for example, or to check the RF output level and provide automatic gain control. The amplifier was designed using a CAD program, which gave the flexibility to use robust optimizer tools for the complete design of the RF chain. Finally, test results are presented that show excellent agreement with the theoretical predictions.
In this paper, we propose a novel variational framework for the reconstruction of dynamic objects from sparse and noisy tomographic data. Using an object-based scene model, we developed a general object dynamic model ...
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ISBN:
(纸本)0780383885
In this paper, we propose a novel variational framework for the reconstruction of dynamic objects from sparse and noisy tomographic data. Using an object-based scene model, we developed a general object dynamic model based on a one to one and differentiable mapping. We then propose a novel distance between curves to incorporate the object dynamics into the variational framework. For the minimization of the energy function, we developed a coordinate descent algorithm based on the level set methods. Experimental results for reconstructing a sequence of multiple dynamic objects are presented.
IP network has been evolving significantly in last decade. Many computers and devices have been attached to the IP network and many applications were taken place over it. One of interesting applications is building em...
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IP network has been evolving significantly in last decade. Many computers and devices have been attached to the IP network and many applications were taken place over it. One of interesting applications is building embedded control system which has connectivity to Internet. This paper explains an implementation of embedded web server with security support which becomes an example of control application over IP network. A security algorithm, TEA (tiny encryption algorithm), has been implemented in a microprocessor system together with TCP/IP stack. The microprocessor system is based on 8051 family microcontroller which serves as web server. The encryption algorithm is processed both on server and client. Therefore in clients need a plug in, which run encryption mechanism, so that they can access the embedded Web server safely.
In the application of curve evolution and level set methods to biomedical image analysis, the incorporation of geometric priors for isolated shapes has been proved useful. On the other hand, the inclusion of a priori ...
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ISBN:
(纸本)0780383885
In the application of curve evolution and level set methods to biomedical image analysis, the incorporation of geometric priors for isolated shapes has been proved useful. On the other hand, the inclusion of a priori topological information concerning the relationship of multiple shapes remains a challenge. In this paper, we propose a differentiable minimin shape distance (DMSD) that is indicative of the topological relation between shapes. A curve evolution equation based on its first variation is derived and this enables us to incorporate this prior into a curve evolution framework. We demonstrate the application of the DMSD by proposing an extension to the Chan-Vese image segmentation model to incorporate topological prior information for challenging image segmentation tasks.
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