With the increasing scale and complexity of the power grid, how to accurately perceive the status of the converter station and detect its abnormality in time has become an urgent problem to be solved. However, the tra...
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In this study, we present a perception algorithm that is based purely on vision or camera data. We focus on demonstrating a powerful end-to-end lane detection method using contemporary computer vision techniques for s...
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In this study, we present a perception algorithm that is based purely on vision or camera data. We focus on demonstrating a powerful end-to-end lane detection method using contemporary computer vision techniques for self-driving cars. We first present a mini-malistic approach based on edge detection and polynomial regression which is the baseline approach for detecting only the straight lane lines. We then propose an improved lane detection technique based on perspective transformations and histogram analysis. In this latter technique, both straight and curved lane lines can be detected. To demonstrate the superiority of the proposed lane detection approach over the conventional approach, simulation results in different environments are presented. (C) 2020 Elsevier Ltd. All rights reserved.
A pattern recognition method based on modified perception algorithm was proposed in this paper. The principle of this method is minimizing the sum of distance between the wrong classified samples and the interface of ...
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ISBN:
(纸本)9783037858943
A pattern recognition method based on modified perception algorithm was proposed in this paper. The principle of this method is minimizing the sum of distance between the wrong classified samples and the interface of different categories, and then the iteration was done with information contained in the minimized errors. The experiment shows that the proposed method can classify the images from Yale, ORL and actual face databases accurately and effectively. The main advantage of the method is that the algorithm is convenient for computer programming, and the recognition rate and recognition time have been distinctly developed.
This paper puts forward a new improved perception algorithm based on solution region by analyzing the pattern's solution geometric characteristic in space. The algorithm could find a better solution vector in solu...
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The applications of computing have led to the diversity of tasks, and one kind of architecture is difficult to adapt several different application tasks. The different requirements of computing resource, storage resou...
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ISBN:
(纸本)9781467371902
The applications of computing have led to the diversity of tasks, and one kind of architecture is difficult to adapt several different application tasks. The different requirements of computing resource, storage resource and communication resource of tasks need to be analyzed, which include the program structure running and extracting the key granularity of the real applications instinct. We can get the sub-algorithm clusters, which have independent function in different fields. Hierarchical hypergraph is used to visually describe the application structure and computing architecture, and the perception algorithm is utilized to get the system states, such as the features of applications, components state information and so on. Then the reconfigurable architecture and decision-making algorithm are utilized to achieve a reasonable matching of the sub-algorithm clusters with sub-structures. A computing instance is analyzed to verify the validity of the reconfigurable architecture. Meanwhile, the graph isomorphism theory is used to show that this diversified architecture reasonable, high-efficiency and low power consumption, while solving different complex applications.
This paper introduces a, learning problem related to the of converting printed documents to ASCII text files.. the goal of the learning procedure is to produce a function that maps documents to restoration techniques ...
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This paper introduces a, learning problem related to the of converting printed documents to ASCII text files.. the goal of the learning procedure is to produce a function that maps documents to restoration techniques in such away that on average the restored documents have, minimum optical character recognition-error. We derive a general form. for the optimal function and Use it to, motivate the, development of a nonparametric method based on nearest neighbors. We also develop a direct method, of solution based on empirical error minimization for which we prove a finite sample bound, on. estimation error that. is independent of distribution. We show that this empirical error minimization problem is, an extension of the empirical optimization problem for traditional M-class classification with general loss function and prove computational hardness for! this problem. We then derive a simple iterative algorithm called generalized multiclass. ratchet (GMR) and, prove that it produces, an optimal function asymptotically (with probability, 1). To obtain the GMR algorithm we introduce a new data map, that extends Kesler's construction for the multiclass problem (see, e.g., [5p, 266]) and then apply an algorithm called Ratchet to this mapped data, Where Ratchet is a,modification of the Pocket algorithm [6]. Finally;we apply these methods to, a collection of documents and report on the experimental results.
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