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Barcodes have been long used for data storage. Detecting and locating barcodes in images of complex background is an essential yet challenging step in the process of automatic barcode reading. This work proposed an algorithm that localizes and segments two-dimensional quick response (QR) barcodes. The localization involved a convolutional neural network that could detect partial QR barcodes. Majority...
In conventional image classification methods, complementary advantages between various single features of images are not fully applied; meanwhile, redundant information exists in the extracted features. As a result, accuracy of image classification is not high. Therefore, a novel approach for image classification based on multi-feature combination and PCA-RBaggSVM (principal component analysis and...
The amount of music information available on the Web is rapidly increasing. There is a pressing need for music information extraction. To extract useful information from natural language text, we must recognize music named entities first. This paper introduces a hybrid method to identify the Chinese named entities in music domain. Recently, machine learning approaches are frequently used to solve...
Support vector machine (SVM) is regarded as a good alternative of the traditional learning classification. Because of its excellent learning performance, it has become a research hot spot in the field of machine learning. This paper describes the new invariant moment feature extraction of SAR objectives based on shape feature, then classify and train the eigenvectors by using SVM. The excellent recognition...
Web document classification is the process of grouping web documents into one or more predefined categories based on their content. It is an important component of web monitor system that can assist people to reduce the dissemination of harmful information. This paper proposes a combined approach for building a decision tree with the multilayer neural network as its categorically value function, and...
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