基于学习方法的事件跟踪系统自动化智能系统综合研究

Balakrishnan Natarajan, Dr.A. Vanitha
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引用次数: 0

摘要

在图像处理中,需要激进方案提出一种从图像中提取所需内容的模型。在各种自动化领域中,提供重要的事实和需求方法起着至关重要的作用。通过遵循稀疏矩阵说明提出的文本内容与图像分离的方法,基于启发式规则对文本成分进行分组并聚类成句。本文对图像分析进行了研究,将视觉项目作为对象和不同的文本模式进行检查。逻辑回归,线性判别分析naïve贝叶斯算法用于预测图像的形式。本文提出了一种学习算法,称为学习向量量化预测算法(LVQ Predict),用于分析图像的部分。提取特征并将其分类为印刷文本和非印刷文本。此外,这些文本被规范化和记录。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Comprehensive Study on Intelligence System for Automatize Event Tracker System Using Learning Method
In image processing, the radical scheme is required to propose a model for extracting the required content from an image. It plays a critical position to offer significant facts and needs methods in various automation arenas. By keeping the way of a parting textual content from images has proposed via following the sparse matrix illustration, grouping text components are based on heuristic rules and clustered into sentence generation. This paper directs a study on image analysis that inspects visual items as objects and different text patterns. Logistic Regression, Linear Discriminant Analysis naïve Bayes Algorithm are used to predict the image forms. This proposed work promotes the learning algorithm called Learning Vector Quantization Prediction Algorithm (LVQ Predict) is used to analysis the parts of the image. The features are extracted and classifies into printed and non-printed texts. Further, these texts are normalized and documented.
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来源期刊
Alinteri Journal of Agriculture Sciences
Alinteri Journal of Agriculture Sciences AGRICULTURE, MULTIDISCIPLINARY-
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