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The goal of image quality assessment (IQA) is to use computational models to measure the consistency between image quality and subjective evaluations. In recent years, convolutional neural networks (CNNs) have been widely used in image processing community and have achieved performance leaps than non CNNs-based methods. In this work, we describe an accurate deep CNNs model for no-reference IQA. Taking...
In the information age, sentiment classification of internet topics is of great significance. This paper proposes a microblog sentiment classification approach with parallel support vector machine (SVM). The proposed method integrates the features of microblog with preprocessing to ensure the data suitable for sentiment classification. After the preprocessing process, Apache Spark parallel SVM is...
Traditional image resizing methods, such as uniform scaling and content-aware image retargeting, are designed to preserve the visually salient contents of an image while resizing it. In this paper, we propose a novel image resizing approach called recognition-oriented image retargeting. Its goal is to preserve the distinctive local features for recognition instead of the traditional visual saliency...
Tongue manifestation is one of the most significant basic criteria for the diagnosis of Traditional Chinese Medicine (TCM). And tongue color recognition with high accuracy will contribute to the efficiency of TCM diagnosis. The drawbacks of traditional tongue diagnosis methods are that the features need to be designed artificially. While the feature acquisition from the deep learning is a process...
For most physical stores, procuring customer behavior data and client management is di cult yet crucial. For stores, especially luxury stores, who value returning customers the most, identifying customer's identity and past purchase history would significantly improve the sales by personalizing the recommendation. Many chain stores utilize membership card to collect purchase information and change...
Nature language processing is an important part in data mining, which counts a lot in the internet age. Feature extraction effects the accuracy of text classification. This paper proposes a method of iterative feature space evolution to optimize the result. Adjusting the extended dictionary and the stop word list, we optimize the feature space time and again to get a better classifier model. The final...
3-D model based objects matching is a fundamental in image processing and computer vision, especially for object localization, tracking, and recognition. In this paper a new deformable models with commonly 9-12 length-angle shape parameters are used for matching, which can represent rich shape details for traffic vehicle classification. A Weighted Modified Square Haudsorff Distance (WMSHD) is designed...
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