There are many kinds of so-called irregular expressions in natural dialogues. Even if the content of a conversation is the same in words, different meanings can be interpreted by a person's feeling or face express...
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There are many kinds of so-called irregular expressions in natural dialogues. Even if the content of a conversation is the same in words, different meanings can be interpreted by a person's feeling or face expression. To have a good understanding of dialogues, it is required in a flexible dialogue processing system to infer the speaker's view properly. However, it is difficult to obtain the meaning of the speaker's sentences in various scenes using traditional methods. In this paper, a new approach for dialogue processing that incorporates information from the speaker's face is presented. We first divide conversation statements into several simple tasks. Second, we process each simple task using an independent processor. Third, we employ some speaker's face information to estimate the view of the speakers to solve ambiguities in dialogues. The approach presented in this paper can work efficiently, because independent processors run in parallel, writing partial results to a shared memory, incorporating partial results at appropriate points, and complementing each other. A parallel algorithm and a method for employing the face information in a dialogue machine translation will be discussed, and some results will be included in this paper.
This paper deals with the implementation of a systolic array architecture in hardware using FPGAs for processing compressed binary images without decompressing them. Specifically, run-length encoding (RLE) is used for...
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This paper deals with the implementation of a systolic array architecture in hardware using FPGAs for processing compressed binary images without decompressing them. Specifically, run-length encoding (RLE) is used for compression. processingimages in compressed form provides a significant speedup in the computation. Using a systolic architecture and implementing it in hardware further increases the speed.
Clustering is a basic operation in imageprocessing and computer vision, and it plays an important role in unsupervised pattern recognition and image segmentation. While there are many methods for clustering, the sing...
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Clustering is a basic operation in imageprocessing and computer vision, and it plays an important role in unsupervised pattern recognition and image segmentation. While there are many methods for clustering, the single-link hierarchical clustering is one of the most popular techniques. In this paper, with the advantages of both optical transmission and electronic computation, we design efficient parallel hierarchical clustering algorithms on the arrays with reconfigurable optical buses (AROB). We first design three efficient basic operations which include the matrix multiplication of two N x N matrices, finding the minimum spanning tree of a graph with N vertices, and identifying the connected component containing a specified vertex. Based on these three data operations, an O(log N) time parallel hierarchical clustering algorithm is proposed using N-3 processors. Furthermore, if the connectivity of the AROB with four-port connection is allowed, two constant time clustering algorithms can be also derived using N-4 and N-3 processors, respectively. These results improve on previously known algorithms developed on various parallel computational models. (C) 2000 Academic Press.
We are interested in running in parallel cellular automata. We present an algorithm which explores the dynamic remapping of cells in order to balance the load between the processing nodes. The parallel application run...
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We are interested in running in parallel cellular automata. We present an algorithm which explores the dynamic remapping of cells in order to balance the load between the processing nodes. The parallel application runs on a cluster of PCs connected by Fast-Ethernet. A general cellular automaton can be described as a set of cells where each cell is a state machine. To compute the next cell state, each cell needs some information from neighbouring cells. There are no limitations on the kind of information exchanged nor on the computation itself. Only the automaton topology defining the neighbours of each cell remains unchanged during the automaton's life. As a typical example of a cellular automaton we consider the image skeletonization problem. Skeletonization requires spatial filtering to be repetitively applied to the image. Each step erodes a thin part of the original image. After the last step, only the image skeleton remains. Skeletonization algorithms require vast amounts of computing power, especially when applied to large images. Therefore, skeletonization application can potentially benefit from the use of parallelprocessing. Two different parallel algorithms are proposed, one with a static load distribution consisting in splitting the cells over several processing nodes and the other with a dynamic load balancing scheme capable of remapping cells during the program execution. Performance measurements shows that the cell migration doesn't reduce the speedup if the program is already load balanced. It greatly improves the performance if the parallel application is not well balanced.
Our purpose is, in medium term, to detect in air images, characteristic shapes and objects such as airports, industrial plants, planes, tanks, trucks, ... with great accuracy and low rate of mistakes. However, we also...
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Our purpose is, in medium term, to detect in air images, characteristic shapes and objects such as airports, industrial plants, planes, tanks, trucks, ... with great accuracy and low rate of mistakes. However, we also want to value whether the link between neural networks and multi-agents systems is relevant and effective. If it appears to be really effective, we hope to use this kind of technology in other fields. That would be an easy and convenient way to depict and to use the agents' knowledge which is distributed and fragmented. After a first phase of preliminary tests to know if agents are able to give relevant information to a neural network, we verify that only a few agents running on an image are enough to inform the network and let it generalize the agents' distributed and fragmented knowledge. In a second phase, we developed a distributed architecture allowing several multi-agents systems running at the same time on different computers with different images. All those agents send information to a `multi neural networks system' whose job is to identify the shapes detected by the agents. The name we gave to our project is Jarod.
This paper studies the application of preconditioned conjugate gradient methods in high resolution color image reconstruction problems. The high resolution color images are reconstructed from multiple undersampled, sh...
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(纸本)0769505716
This paper studies the application of preconditioned conjugate gradient methods in high resolution color image reconstruction problems. The high resolution color images are reconstructed from multiple undersampled, shifted, degraded color frames with subpixel displacements. The resulting degradation matrices are spatially variant. The preconditioners are derived by taking the cosine transform approximation of the degradation matrices. The resulting preconditioning matrices allow the use of fast transform methods. We show how the methods can be implemented on parallel computers, and toe demonstrate thee's parallel efficiency using experiments on a sixteen processor IBM SP-2.
A multi-tolerance region-growing algorithm for automatically detecting and circumscribing calcifications in digitized mammographic images was developed. Independent studies comparing various segmentation methods showe...
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A multi-tolerance region-growing algorithm for automatically detecting and circumscribing calcifications in digitized mammographic images was developed. Independent studies comparing various segmentation methods showed that the multi-tolerance technique works well. However, the method is computationally expensive due to the checking of the validity of the grown region at every tolerance level until the optimal region is obtained for each calcification. Furthermore, a single mammogram may contain as many as a few hundred calcifications. In order to reduce the processing time, the calcification detection algorithm was implemented on a cluster of processors using the message passing interface. In the parallel implementation, the master processor partitions the image via histogram thresholding, and sends seed pixels to the slaves to execute the multi-tolerance region-growing procedure. The slave processors grow regions, calculating a few shape parameters at each tolerance level. The parameters are used to compute distance measures which are compared until the minimum change in distance is achieved. Shape factors are then computed to describe the roughness of each region's final boundary and returned to the master processor. Initial trials have shown a speedup factor of three to eight when comparing the use of 13 slave processors to the use of one slave processor.
Obtaining the listening rates of radio stations in function of time is an important instrument for determining the impact of publicity. Since many radio stations are financed by publicity, the exact determination of r...
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Obtaining the listening rates of radio stations in function of time is an important instrument for determining the impact of publicity. Since many radio stations are financed by publicity, the exact determination of radio listening rates is vital to their existence and to their further development. Existing methods of determining radio listening rates are based on face to face interviews or telephonic interviews made with a sample population. These traditional methods however require the cooperation and compliance of the participants. In order to significantly improve the determination of radio listening rates, special watches were created which incorporate a custom integrated circuit sampling the ambient sound during a few seconds every minute. Each watch accumulates these compressed sound samples during one full week. Watches are then sent to an evaluation center, where the sound samples are matched with the sound samples recorded from candidate radio stations. The present paper describes the processing steps necessary for computing the radio listening rates, and shows how this application was parallelized on a cluster of PCs using the CAP Computer-aided parallelization framework. Since the application must run in a production environment, the paper describes also the support provided for graceful degradation in case of transient or permanent failure of one of the system's components. The parallel sound matching server offers a linear speedup up to a large number of processing nodes thanks to the fact that disk access operations across the network are done in pipeline with computations.
A parallel implementation of the 2D discrete wavelet transform on a distributed memory multiprocessor system called PARNEU is presented. The mapping has been chosen with consideration to load balancing and communicati...
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A parallel implementation of the 2D discrete wavelet transform on a distributed memory multiprocessor system called PARNEU is presented. The mapping has been chosen with consideration to load balancing and communication methods in order to achieve the best possible scalability and performance in transforming one single image. Detailed performance figures are included. Experimental results show that significant parallel speedup is reached with this mapping.
This paper reports on results from an ongoing project to develop methods for representing and managing multiple, concurrent levels of modeling detail and enabling high performance computing, namely parallelprocessing...
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This paper reports on results from an ongoing project to develop methods for representing and managing multiple, concurrent levels of modeling detail and enabling high performance computing, namely parallelprocessing, within object-based simulation frameworks such as HLA. We present here the interface structure and runtime support service concept for using parallel arrays for high performance computing within distributed object-based simulation frameworks. The approach employs a distributed array descriptor, which can be a basis for extending the HLA standard to provide support for efficiently sharing very large data arrays or sub-arrays among federates. The goal is to reduce communications overhead and thereby improve simulation performance involving C4ISR models that require, for example, interpolation and extrapolation of large data sets, such as those that naturally occur for overlay, coupling, and fusion of phenomenology information in multi-sensor networks.
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