The Experts below are selected from a list of 10257 Experts worldwide ranked by ideXlab platform
Yen-ping Chen - One of the best experts on this subject based on the ideXlab platform.
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online classifier Construction Algorithm for human activity detection using a tri axial accelerometer
International Conference on Intelligent Computing, 2008Co-Authors: Yen-ping Chen, Jhunying Yang, Shunnan Liou, Jeen-shing WangAbstract:This paper presents an online Construction Algorithm for constructing fuzzy basis function (FBF) classifiers that are capable of recognizing different types of human daily activities using a tri-axial accelerometer. The activity recognition is based on the acceleration data collected from a wireless tri-axial accelerometer module mounted on users' dominant wrists. Our objective is to enable users to: (1) online add new training samples to the existing classes for increasing the recognition accuracy, (2) online add additional classes to be recognized, and (3) online delete an existing class. For this objective we proposed a dynamic linear discriminant analysis (LDA) which can dynamically update the scatter matrices for online constructing FBF classifiers without storing all the training samples in memory. Our experimental results have successfully validated the integration of the FBF classifier with the proposed dynamic LDA can reduce computational burden and achieve satisfactory recognition accuracy.
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FUZZ-IEEE - A Hammerstein Neuro-Fuzzy Network with an Online Hybrid Construction Algorithm for Dynamic Applications
2006 IEEE International Conference on Fuzzy Systems, 2006Co-Authors: Jeen-shing Wang, Yen-ping ChenAbstract:This paper presents a Hammerstein neuro-fuzzy network with an online hybrid Construction Algorithm for dealing with dynamic applications. The proposed recurrent neuro-fuzzy system possesses two salient features: 1) it is capable of translating the complicated dynamic behavior of a system into a set of simple linguistic "dynamic" rules and into a state-space representation as well, and 2) with an automated hybrid Construction Algorithm, it can self-construct it network structure with a parsimonious size and satisfactory learning performance. Extensive computer simulations have been conducted to validate the effectiveness of the proposed approach for dynamic applications.
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A Hammerstein Neuro-Fuzzy Network with an Online Hybrid Construction Algorithm for Dynamic Applications
2006 IEEE International Conference on Fuzzy Systems, 2006Co-Authors: Jeen-shing Wang, Yen-ping ChenAbstract:This paper presents a Hammerstein neuro-fuzzy network with an online hybrid Construction Algorithm for dealing with dynamic applications. The proposed recurrent neuro-fuzzy system possesses two salient features: 1) it is capable of translating the complicated dynamic behavior of a system into a set of simple linguistic "dynamic" rules and into a state-space representation as well, and 2) with an automated hybrid Construction Algorithm, it can self-construct it network structure with a parsimonious size and satisfactory learning performance. Extensive computer simulations have been conducted to validate the effectiveness of the proposed approach for dynamic applications.
Sharma V. Thankachan - One of the best experts on this subject based on the ideXlab platform.
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CPM - Space-Efficient Construction Algorithm for the Circular Suffix Tree
Combinatorial Pattern Matching, 2013Co-Authors: Tsung-han Ku, Rahul Shah, Sharma V. ThankachanAbstract:Hon et al. (2011) proposed a variant of the suffix tree, called circular suffix tree, and showed that it can be stored succinctly and can be used to solve the circular dictionary matching problem efficiently. In this paper, we give the first Construction Algorithm for the circular suffix tree, which takes O(nlogn) time and requires O(nlogσ + dlogn) bits of working space, where n is the total length of the patterns in \(\mathcal D\), d is the number of patterns in \(\mathcal{D}\), and σ is the alphabet size.
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Space-Efficient Construction Algorithm for the Circular Suffix Tree
2013 Data Compression Conference, 2013Co-Authors: Tsung-han Ku, Rahul Shah, Sharma V. ThankachanAbstract:Hon et al. (2011) recently proposed a variant of suffix tree, called circular suffix tree, and showed that it can be compressed into succinct space and can be used to solve the circular dictionary matching problem efficiently. Although there are several efficient Construction Algorithms for the suffix tree in the literature, none of them can be applied directly to construct circular suffix tree due to the different nature of the patterns being indexed. Here, we give the first Construction Algorithm for the circular suffix tree, which takes O(n log n) time and requires O(n log σ + d log n)$ bits of working space, where n denotes the total length of the patterns in the dictionary, d denotes the number of patterns, and s denotes the alphabet size.
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DCC - Space-Efficient Construction Algorithm for the Circular Suffix Tree
2013 Data Compression Conference, 2013Co-Authors: Tsung-han Ku, Rahul Shah, Sharma V. ThankachanAbstract:Hon et al. (2011) recently proposed a variant of suffix tree, called circular suffix tree, and showed that it can be compressed into succinct space and can be used to solve the circular dictionary matching problem efficiently. Although there are several efficient Construction Algorithms for the suffix tree in the literature, none of them can be applied directly to construct circular suffix tree due to the different nature of the patterns being indexed. Here, we give the first Construction Algorithm for the circular suffix tree, which takes O(n log n) time and requires O(n log σ + d log n)$ bits of working space, where n denotes the total length of the patterns in the dictionary, d denotes the number of patterns, and s denotes the alphabet size.
Ulrich Lang - One of the best experts on this subject based on the ideXlab platform.
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A Linear Time BVH Construction Algorithm for Sparse Volumes
2019 IEEE Pacific Visualization Symposium (PacificVis), 2019Co-Authors: Stefan Zellmann, Matthias Hellmann, Ulrich LangAbstract:While fast spatial index Construction for triangle meshes has gained a lot of attention from the research community in recent years, fast tree Construction Algorithms for volume data are still rare and usually do not focus on real-time processing. We propose a linear time bounding volume hierarchy Construction Algorithm based on a popular method for surface ray tracing of triangle meshes that we adapt for direct volume rendering with sparse volumes. We aim at interactive to real-time Construction rates and evaluate our Algorithm using a GPU implementation.
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PacificVis - A Linear Time BVH Construction Algorithm for Sparse Volumes
2019 IEEE Pacific Visualization Symposium (PacificVis), 2019Co-Authors: Stefan Zellmannn, Matthias Hellmann, Ulrich LangAbstract:While fast spatial index Construction for triangle meshes has gained a lot of attention from the research community in recent years, fast tree Construction Algorithms for volume data are still rare and usually do not focus on real-time processing. We propose a linear time bounding volume hierarchy Construction Algorithm based on a popular method for surface ray tracing of triangle meshes that we adapt for direct volume rendering with sparse volumes. We aim at interactive to real-time Construction rates and evaluate our Algorithm using a GPU implementation.
Jeen-shing Wang - One of the best experts on this subject based on the ideXlab platform.
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online classifier Construction Algorithm for human activity detection using a tri axial accelerometer
International Conference on Intelligent Computing, 2008Co-Authors: Yen-ping Chen, Jhunying Yang, Shunnan Liou, Jeen-shing WangAbstract:This paper presents an online Construction Algorithm for constructing fuzzy basis function (FBF) classifiers that are capable of recognizing different types of human daily activities using a tri-axial accelerometer. The activity recognition is based on the acceleration data collected from a wireless tri-axial accelerometer module mounted on users' dominant wrists. Our objective is to enable users to: (1) online add new training samples to the existing classes for increasing the recognition accuracy, (2) online add additional classes to be recognized, and (3) online delete an existing class. For this objective we proposed a dynamic linear discriminant analysis (LDA) which can dynamically update the scatter matrices for online constructing FBF classifiers without storing all the training samples in memory. Our experimental results have successfully validated the integration of the FBF classifier with the proposed dynamic LDA can reduce computational burden and achieve satisfactory recognition accuracy.
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FUZZ-IEEE - A Hammerstein Neuro-Fuzzy Network with an Online Hybrid Construction Algorithm for Dynamic Applications
2006 IEEE International Conference on Fuzzy Systems, 2006Co-Authors: Jeen-shing Wang, Yen-ping ChenAbstract:This paper presents a Hammerstein neuro-fuzzy network with an online hybrid Construction Algorithm for dealing with dynamic applications. The proposed recurrent neuro-fuzzy system possesses two salient features: 1) it is capable of translating the complicated dynamic behavior of a system into a set of simple linguistic "dynamic" rules and into a state-space representation as well, and 2) with an automated hybrid Construction Algorithm, it can self-construct it network structure with a parsimonious size and satisfactory learning performance. Extensive computer simulations have been conducted to validate the effectiveness of the proposed approach for dynamic applications.
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A Hammerstein Neuro-Fuzzy Network with an Online Hybrid Construction Algorithm for Dynamic Applications
2006 IEEE International Conference on Fuzzy Systems, 2006Co-Authors: Jeen-shing Wang, Yen-ping ChenAbstract:This paper presents a Hammerstein neuro-fuzzy network with an online hybrid Construction Algorithm for dealing with dynamic applications. The proposed recurrent neuro-fuzzy system possesses two salient features: 1) it is capable of translating the complicated dynamic behavior of a system into a set of simple linguistic "dynamic" rules and into a state-space representation as well, and 2) with an automated hybrid Construction Algorithm, it can self-construct it network structure with a parsimonious size and satisfactory learning performance. Extensive computer simulations have been conducted to validate the effectiveness of the proposed approach for dynamic applications.
Kuo-tang Tsai - One of the best experts on this subject based on the ideXlab platform.
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Belt-barrier Construction Algorithm for WVSNs
2012 IEEE Wireless Communications and Networking Conference (WCNC), 2012Co-Authors: Chien-fu Cheng, Kuo-tang TsaiAbstract:Previous research of barrier coverage did not consider breadth of coverage in Wireless Visual Sensor Networks (WVSNs). In this paper, we consider breadth to increase the Quality of Monitor (QoM) of WVSNs. The proposed Algorithm is called Distributed β-Breadth Belt-Barrier Construction Algorithm (D-TriB). D-TriB constructs a belt-barrier with β breadth to offer β level of QoM, we call β-QoM. D-TriB can not only reduce the number of camera sensors required to construct a barrier but also ensure that any barrier with β-QoM in the network can be identified. Finally, the successful rate of the proposed Algorithm is evaluated through simulations.
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WCNC - Belt-barrier Construction Algorithm for WVSNs
2012 IEEE Wireless Communications and Networking Conference (WCNC), 2012Co-Authors: Chien-fu Cheng, Kuo-tang TsaiAbstract:Previous research of barrier coverage did not consider breadth of coverage in Wireless Visual Sensor Networks (WVSNs). In this paper, we consider breadth to increase the Quality of Monitor (QoM) of WVSNs. The proposed Algorithm is called Distributed β-Breadth Belt-Barrier Construction Algorithm (D-TriB). D-TriB constructs a belt-barrier with β breadth to offer β level of QoM, we call β-QoM. D-TriB can not only reduce the number of camera sensors required to construct a barrier but also ensure that any barrier with β-QoM in the network can be identified. Finally, the successful rate of the proposed Algorithm is evaluated through simulations.
