Classification of texture pattern is one of the most important problems in patternrecognition. In this paper, we present a classification method based on the Discrete Cosine Transform (DCT) coefficients of texture im...
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Classification of texture pattern is one of the most important problems in patternrecognition. In this paper, we present a classification method based on the Discrete Cosine Transform (DCT) coefficients of texture image. As the DCT works on gray level image, the color scheme of each image is transformed into gray levels. For classifying the images with DCT, we used two popular soft computing techniques namely neurocomputing and neuro-fuzzy computing. We used a feedforward neural network trained by backpropagation algorithm and an evolving fuzzy neural network to classify the textures. the soft computing models were trained using 80% of the texture data and remaining was used for testing and validation purposes. A performance comparison was made among the soft computing models for the texture classification problem. We also analyzed the effects of prolonged training of neural networks. It is observed that the proposed neuro-fuzzy model performed better than neural network.
the paper is devoted to implementation and exploration of evolutionary development of the short-term memory mechanism in spiking neural networks (SNN) starting from initial chaotic state. Short-term memory is defined ...
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ISBN:
(纸本)9783642202810
the paper is devoted to implementation and exploration of evolutionary development of the short-term memory mechanism in spiking neural networks (SNN) starting from initial chaotic state. Short-term memory is defined here as a network ability to store information about recent stimuli in form of specific neuron activity patterns. Stable appearance of this effect was demonstrated for so called stabilizing SNN, the network model proposed by the author. In order to show the desired evolutionary behavior the network should have a specific topology determined by "horizontal" layers and "vertical" columns.
Task scheduling has been a key issue to improve parallel execution in distributed systems. Master-Slave task scheduling, as a technique of mapping and scheduling loads to heterogeneous platforms, has aroused interests...
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ISBN:
(纸本)9780769533520
Task scheduling has been a key issue to improve parallel execution in distributed systems. Master-Slave task scheduling, as a technique of mapping and scheduling loads to heterogeneous platforms, has aroused interests of many researchers. Although minimizing the Master-Slave application's makespan (the overall completion time) in general case is a NP-complete problem, it is still meaningful in some special fields. In this paper, we aim at improving the performance of the Master-Slave pattern applications in the case with a large number of equal-sized and independent tasks and propose a new strategy EOMT (Equilibrium Overhead with Multi-cycle Tasking) for task scheduling in the grid environment. the EOMT strategy is designed for the grid environment with heterogeneous resources. the main concept of EOMT is to make the workload assigned to each slave node as even as possible to reduce applications makespan. A detailed analysis for Master-Slave task scheduling is given in this paper. Experiment results show that our strategy outperforms other traditional task scheduling strategies in different computation and network resource combinations in the grid environment.
Security has become a significant factor of Internet of things (IoT) and Cyber Physical Systems (CPS) wherein the devices usually vary in computing power and intrinsic hardware features. It is necessary to use securit...
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Cloud computing is taking as exciting technology because of its economic behavior. the major issue in the cloud is its security because it is far from end-user a new thing applied science is developed called fog compu...
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Computer Assisted Visual Interactive recognition (CAVIAR) draws on sequential patternrecognition, image database, expert systems, pen computing, and digital camera technology. It is designed to recognize wild flowers...
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ISBN:
(纸本)076951695X
Computer Assisted Visual Interactive recognition (CAVIAR) draws on sequential patternrecognition, image database, expert systems, pen computing, and digital camera technology. It is designed to recognize wild flowers and other families of similar objects more accurately than machine vision and faster than most laypersons. the novelty of the approach is that human perceptual ability is exploited through interaction withthe image of the unknown object. the computer remembers the characteristics of all previously seen classes, suggests possible operator actions, and displays confidence scores based on already detected features. In one application, consisting of 80 test images of wild flowers, 10 laypersons averaged 80% recognition accuracy, at 12 seconds per flower.
We address the problem of the similarity search in large multidimensional sequence databases. Most of previous work focused on similarity matching and retrieval of one-dimensional sequences, However, many new applicat...
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ISBN:
(纸本)3540286608
We address the problem of the similarity search in large multidimensional sequence databases. Most of previous work focused on similarity matching and retrieval of one-dimensional sequences, However, many new applications such as weather data or music databases need to handle multidimensional sequences. In this paper, we present the efficient search method for finding similar sequences to a given query sequence in multidimensional sequence databases. the proposed method can efficiently reduce the search space and guarantees no false dismissals. We give preliminary experimental results to show the effectiveness of the proposed method.
On-demand resource provisioning is with great challenge in cloud systems. the key problem is how to learn about the future workload in advance to help determine resource allocation. there are various prediction models...
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In most Service-Oriented frameworks service selection is based on provider-centric information despite well-known shortcomings (trustworthiness, incompleteness, subjectivity). We propose to allow consumers and third-p...
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there is a significant need for a realistic dataset on which to evaluate layout analysis methods and examine their performance in detail. this paper presents a new dataset (and the methodology used to create it) based...
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