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- 저자 : Weilan Wang (검색결과 4 건)
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Tiejun Wang,Weilan Wang 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.1
With the fast development of data analysis and computer science technology, the design and implementation of image retrieval system has been a hot topic. The prior research focus more on image-size based approaches which are not intelligent or convenient. In this paper, we present a novel modified evolutionary algorithm based image retrieval framework theoretically with applications. To achieve more accuracy in less number of iteration, this paper, proposed a new approach to enhance the performance of content guided retrieval methodology by improving the performance of RF through Particle Swarm Optimization, Genetic Algorithm and Support Vector Machine. The objective of using Genetic Algorithm and Particle Swarm Optimization is to increase the number of images in relevant set where SVM is used to classify the relevant and irrelevant images. The experimental and numerical simulation indicate the efficiency of our method which means the presented technique is helpful in the fields where high accuracy rate of image retrieval is required. Further work of interest is also discussed in the final section.
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Tiejun Wang,Weilan Wang 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.1
Because of the feature points can describe the local characteristics of the image in a reasonable manner, effective use of feature point of content based image retrieval become the current hot issues in the field of computer vision. Aiming at this problem, we put forward a kind of combination clustering based on feature points, a new method of image retrieval. The method includes the combination of feature point clustering algorithm and based on the algorithm of local color histogram construction strategy. With the existing and local color histogram retrieval method based on feature points, compared to the method can effectively solve the current method of feature point location information and feature point center relying too much on the problem. Subjectivity and as a result of the manual annotation image accuracy, the traditional image retrieval methods cannot meet the needs of the user. Multidimensional indexing technology is only from the perspective of how to improve the indexing algorithm to adapt to the large-scale database to consider a problem, in content-based image retrieval. Our research combines the advantages of the semantic analysis and kernel clustering which will enhance the performance of the traditional image retrieval methods and strengthen the feasibility of the algorithm.
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Kinetics of polyvinyl butyral hydrolysis in ethanol/water solutions
Wenwen Luan,Chunyu Wang,Zuoxiang Zeng,Weilan Xue,Xuelian He,Yu Bai 한국화학공학회 2021 Korean Journal of Chemical Engineering Vol.38 No.9
The hydrolysis kinetics of polyvinyl butyral (PVB) was studied in ethanol/water mixed solvents in the temperature range of 339.15-355.15 K, and a three-step hypothesis was proposed to describe the hydrolysis process. The influences of stirring speed, ethanol content and temperature on the hydrolysis of PVB were investigated, and an induction period (IP) phenomenon was found in the process of PVB hydrolysis. The ethanol content in the mixed solvents has a great influence on IP, which is due to the formation of the two kinds of water-ethanol clusters in the system. Temperature influences the IP by changing the catalytic activity of hydroxylamine hydrochloride (HH) on the hydrolysis of PVB. The shrinking core models with three controlling steps were used to fit the kinetic data, and the results indicate that the model controlled by chemical reaction is suitable to describe the kinetic behavior of PVB hydrolysis.
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Patch size adaptive image inpainting
( Huaming Liu ),( Guanming Lu ),( Xuehui Bi ),( Weilan Wang ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.10
Texture synthesis technology has the advantages of repairing texture and structure at the same time. However, during the filling process, the size of the patch is fixed, and the content of the filling is not fully considered. In order to be able to adaptively change the patch size, we used the exemplar-based inpainting technique as the test algorithm, considering the image structure and texture, calculated the image structure patch size and texture patch size, and comprehensively determined the image patch size. This can adaptively change the patch size according to the filling content. In addition, we use multi-layer images to calculate the priority, so that the order of image repair was more stable. The proposed repair algorithm is compared with other image repair algorithms. The experimental results showed that the proposed adaptive image repair algorithm can better repair the texture and structure of the image, which proved the effectiveness of the proposed algorithm.
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