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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...
Convolutional neural networks (CNNs) have been widely used in image processing community. Image deblocking is a post-processing strategy, which aims to reduce the visually annoying blocking artifacts that are caused by block-based transform coding at low bit rates. In recent years, CNNs based methods have been proposed to solve this classic image processing problem. In this paper, we present an efficient...
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...
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...
Tongue coating nature inspection is an essential part in the tongue diagnosis of Traditional Chinese Medicine (TCM). However, it has been depending on doctors' visual judgment. Although many researches have been done in this field, the issue remains challenging. The approaches are limited to image processing or shallow neural networks. In this paper, we propose to computerize tongue coating nature...
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...
Support vector machine (SVM) is a popular classifier dealing with small-scale datasets. It has outstanding performance compared to other classifiers. However the execution time is extremely long when training Big Data. The Graphics Processing Unit (GPU) is a massively parallel device which performs very well as a co-processor. NVIDIA proposed a programming platform, CUDA, in 2006, which makes it much...
This paper demonstrates the linkage between logistics system simulation and teaching mode, and explores new teaching methods and teaching ideas. It puts emphasis on analyzing the application of logistics simulation technology in the logistics system and exploring appropriate teaching modes of logistics system simulation. We make a point of the application of logistics system theory knowledge and the...
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