Institution
Chung Yuan Christian University
Education•Taoyuan City, Taiwan•
About: Chung Yuan Christian University is a education organization based out in Taoyuan City, Taiwan. It is known for research contribution in the topics: Membrane & Fuzzy logic. The organization has 9819 authors who have published 11623 publications receiving 213139 citations. The organization is also known as: Tiong-gôan-tāi-ha̍k & CYCU.
Topics: Membrane, Fuzzy logic, Adsorption, Control theory, Photoluminescence
Papers published on a yearly basis
Papers
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TL;DR: A new similarity measure for IFSs induced by the Jaccard index is proposed and a clustering procedure is proposed by combining the proposed similarity measure with a robust clustering method for analyzing IFS data sets.
Abstract: A similarity measure is a useful tool for determining the similarity between two objects. Although there are many different similarity measures among the intuitionistic fuzzy sets (IFSs) proposed in the literature, the Jaccard index has yet to be considered as way to define them. The Jaccard index is a statistic used for comparing the similarity and diversity of sample sets. In this study, we propose a new similarity measure for IFSs induced by the Jaccard index. According to our results, proposed similarity measures between IFSs based on the Jaccard index present better properties. Several examples are used to compare the proposed approach with several existing methods. Numerical results show that the proposed measures are more reasonable than these existing measures. On the other hand, measuring the similarity between IFSs is also important in clustering. Thus, we also propose a clustering procedure by combining the proposed similarity measure with a robust clustering method for analyzing IFS data sets. We also compare the proposed clustering procedure with two clustering methods for IFS data sets.
71 citations
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TL;DR: Noninvasive application of the generalized transfer function techniques produces estimates ofSBP-C and PP-C with errors equivalent to those of the oscillometric blood pressure monitor in the estimation of SBP-B andPP-B.
71 citations
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TL;DR: The MD and MC results demonstrate good agreement with the experimental data, validating the feasibility of molecular simulation techniques in PV membranes at the molecular scale.
70 citations
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TL;DR: This paper presents the usage of a trained deep convolutional neural network model to extract the features of the images, and then, used the AdaBoost algorithm to assemble the Softmax classifiers into recognizable images, resulting in a 3% increase of accuracy of the trained CNN models.
Abstract: Convolutional neural networks (CNNs), which are composed of multiple processing layers to learn the representations of data with multiple abstract levels, are the most successful machine learning models in recent years. However, these models can have millions of parameters and many layers, which are difficult to train, and sometimes several days or weeks are required to tune the parameters. Within this paper, we present the usage of a trained deep convolutional neural network model to extract the features of the images, and then, used the AdaBoost algorithm to assemble the Softmax classifiers into recognizable images. This method resulted in a 3% increase of accuracy of the trained CNN models, and dramatically reduced the retraining time cost, and thus, it has good application prospects.
70 citations
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21 May 2006TL;DR: A new video-based surveillance system that can perform real-time event detection if a number of wanted trajectories are pre-stored in a video surveillance system and an algorithm to merge these trajectories into a representative one is proposed.
Abstract: In recent years, real-time direct detection of events by surveillance systems has attracted a great deal of attention. In this paper, we propose a new video-based surveillance system that can perform real-time event detection. In the background modeling phase, we adopt a mixture of Gaussian approach to determine the background. Meanwhile, we use color blob-based tracking to track foreground objects. Due to the self-occlusion problem, the tracking module is designed as a multi-blob tracking process to obtain similar multiple trajectories. We devise an algorithm to merge these trajectories into a representative one. After applying the Douglas-Peucker algorithm to approximate a trajectory, we can compare two arbitrary trajectories. The above mechanism enables us to conduct real-time event detection if a number of wanted trajectories are pre-stored in a video surveillance system.
70 citations
Authors
Showing all 9844 results
Name | H-index | Papers | Citations |
---|---|---|---|
Simon Lin | 126 | 754 | 69084 |
Xiaodong Li | 104 | 1300 | 49024 |
Yu Wang | 92 | 1687 | 47472 |
Leaf Huang | 92 | 350 | 25867 |
Duu-Jong Lee | 91 | 979 | 37292 |
Yen Wei | 85 | 649 | 25805 |
Ru-Shi Liu | 82 | 738 | 26699 |
Kazuhiko Ishihara | 77 | 713 | 24795 |
Gwo-Hshiung Tzeng | 77 | 465 | 26807 |
Huan-Tsung Chang | 76 | 405 | 21476 |
Hari M. Srivastava | 76 | 1126 | 42635 |
Jianhua Yang | 74 | 554 | 27839 |
Yen Wei | 68 | 309 | 17527 |
Hsisheng Teng | 67 | 213 | 14408 |
Kevin C.-W. Wu | 66 | 278 | 15193 |