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A parallel neural network algorithm based on BP and RBF neural network for solving inverse kinematics of robot is proposed in this paper. Concrete steps of this method and related matters that should be noticed are presented. BP network is trained by LM algorithm and RBF network increases radial basis neurons automatically. The simulation results of PUMA560 show that this algorithm is simple and reliable,...
This paper presents a hybrid method for detecting and localizing texts in natural scene images by stroke segmentation, verification and grouping. To improve system performance, novelties on two aspects are proposed: 1) a scale-adaptive segmentation method is designed for extracting stroke candidates, and 2) a CRF model with pair-wise weight by local line fitting is designed for stroke verification...
The prediction strength of cement is an important task in civil engineering. In this study, the support vector machine (SVM), a novel type of learning algorithm based on statistical theory, has been used to predict the 28d strength of cement. The seven input variables used for the SVM model for prediction of strength are content of slag, SO3 content, cement fineness, 1d compressive strength and folding...
In the wake of awareness for health issues, people have paid more and more attention to the health investment for themselves. In recent years, joining the fitness clubs has been a popular way for people to invest health. Fitness clubs' investment environment has a significant impact on the health investment benefit of the consumers and profit of fitness clubs. Therefore, fitness clubs' investment...
This paper proposes a new method for fast text localization in natural scene images by combining learning-based region filtering and verification in a coarse-to-fine strategy. In each pyramid layer, a boosted region filter is used to extract candidate text regions, which are segmented into candidate text lines by multi-orientation projection analysis. A polynomial classifier with combined features...
This paper proposes a novel hybrid method to robustly and accurately localize texts in natural scene images. A text region detector is designed to generate a text confidence map, based on which text components can be segmented by local binarization approach. A conditional random field (CRF) model, considering the unary component property as well as binary neighboring component relationship, is then...
In this paper, we present a robust system to accurately detect and localize texts in natural scene images. For text detection, a region-based method utilizing multiple features and cascade AdaBoost classifier is adopted. For text localization, a window grouping method integrating text line competition analysis is used to generate text lines. Then within each text line, local binarization is used to...
This paper presents a novel classified method that is called extension genetic algorithm (EGA). The new method is a combination of extension theory and genetic algorithm (GA). In the past, we used the extension method in some clustered problems. With the method, we had to rely on experiences to set rules on classical domain and weight, which caused to increase two tedious and complicated steps in...
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