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检索条件"机构=Image Processing and Intelligent Control Key Laboratory"

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Pre-extracting boundary vectors for support vector machine using pseudo-density estimation method

Pre-extracting boundary vectors for support vector machine u...

引用

MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Zhang, Li Zhou, Weida Chen, Guirong Zhou, Hongjie Ye, Ning Jiao, Licheng Institute of Intelligent Information Processing Key Laboratory of Intelligent Perception and Image Understanding Xidian University 710071 China

ISBN: (纸本)9780819478078

Support vector machines (SVMs) have become useful and universal learning machines. SVMs construct a decision function by support vectors (SVs) and their corresponding weights. The training phase of SVMs definitely uses all training samples, which leads to a large computational complexity for a large scale sample set. Moreover support vectors could not be found until a quadratic programming (QP) problem is solved. Actually we know only SVs play a role in the decision function. Hence, pseudo density estimation (PDE) is presented to extract a set of boundary vectors (BVs) which may contain SVs. The PDE method is a variant of Parzen window method. Hyperspheres are considered as the window functions. In our method, for each sample we construct a hypersphere with an unfixed radius. The ratio of the number of samples contained in the hypersphere of a sample to the total training samples can be taken as the pseudo density of the corresponding sample. The set of BVs is taken as the training input to SVMs. In doing so, it speeds the training procedure of SVMs. It is convenient for PDE to determine its parameter. The experiments show that SVMs using PDE have the similar generalization performance to SVMs. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Support vector machines

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H∞ based decoupling tracking control of hypersonic vehicle 19

H∞ based decoupling tracking control of hypersonic vehicle

引用

19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Lan, Xuejing Wang, Zhishen Liu, Lei Wang, Yongji School of Automation Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9783902823625

The H∞ based decoupling tracking control is studied in this paper. A virtual system constituted by the controlled system and the no coupling reference model is firstly set up. The controlled system is driven to follow the reference model to realize the decoupling. And the tracking error can be formulated by the H∞ norm of the virtual system. Then the controller is derived by minimizing the H∞ norm, which can be described by Linear Matrix Inequalities (LMIs). The necessary and sufficient condition of existence of controller is derived based on the LMIs above. A flight control example is given to illustrate the effectiveness of the proposed method. The simulation results show that the proposed method is of better control performance than Linear Quadratic (LQ) tracking controller. © IFAC.

关键词： controllers

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Fabric Defect Defection based on Lightweight Convolutional Denoising Auto-Encoder 22

Fabric Defect Defection based on Lightweight Convolutional D...

引用

8th International Conference on Computing and Artificial Intelligence, ICCAI 2022

作者： Jin, Dong Li, Wenzheng Sun, Zhigang Li, Xiao School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781450396110

In the industrial production environment, the scarcity of defect samples and the high labor cost of labeling defect samples make supervised machine learning models difficult to implement. In addition, defect detection using deep learning models usually requires high computation cost and advanced hardware platform, which is not suitable for running on embedded platforms. To solve this problem, this paper proposes an unsupervised fabric defect detection method based on lightweight convolutional denoising auto-encoder(LCDAE). The LCDAE model is constructed by the bottleneck layer in MobileNetV3. Experimental results show that the method can effectively detect and localize defects with less computation and has the potential to perform defect detection on edge-embedded platforms. © 2022 ACM.

关键词： Defects

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An optimal software maintenance policy based on reliability and risk

An optimal software maintenance policy based on reliability ...

引用

2014 International Joint Conference on Neural Networks, IJCNN 2014

作者： Xiaoping, Wang Fang, Zhou Yi, Shen School of Automation Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781479914845

Software maintenance is assuming ever more a crucial role in the lifecycle of software due to the increase of software requirements and the high variability of software environment. Common approaches of studying software maintenance are to consider them as a static by-product of software operation and only the maintenance cost is covered. In this paper, software maintenance policies are studied with the consideration of software reliability and risk. An optimization model is defined to drive the choice of a maintenance schedule. The solution of the model provides the best maintenance policy and the choice of actual actions that will minimize the average maintenance cost while the software reliability and risk are acceptable. Finally, a numerical example is given to show the analysis process of our proposed policy. © 2014 IEEE.

关键词： Software reliability

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K-means selective cluster ensembles based on multiple feature subsets

K-means selective cluster ensembles based on multiple featur...

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MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Zhang, Li Zhou, Weida Zou, Haishuang Huo, Jieting Wu, Caili Jiao, Licheng Institute of Intelligent Information Processing Key Laboratory of Intelligent Perception and Image Understanding Xidian University 710071 China

ISBN: (纸本)9780819478078

Combining multiple clusterers is emerged as a powerful method for improving both the robustness and the stability of unsupervised classification solutions. In this paper, k-means selective cluster ensembles based on multiple feature subsets are proposed. In the ensemble, a random subset of features is used to train an individual k-means clusterer. In the final step, the selective weighted voting scheme is used for finding the best partition. The consensus function is constructed by relabeling all partitions of clusterers and finding the best partition. Experimental results on 4 UCI data sets show that our ensemble method can improve the clustering performance. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Set theory

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image Sample Generation of Stator Surface Defects Based on Layer Mask Blending Generative Adversarial Network 23

Image Sample Generation of Stator Surface Defects Based on L...

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9th International Conference on Computing and Artificial Intelligence, ICCAI 2023

作者： Li, Wenzheng Tian, Lihua Sun, Zhigang Xiao, Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781450399029

In industrial production processes, defect inspection plays an important role in reducing the occurrence of failures and improving production efficiency. Data-driven algorithms represented by deep learning have made great progress in recent years, but need to face the problems of small quantity and poor quality of datasets when applied to industrial defect inspection. This paper proposes a layer mask blending-based generative adversarial network (LMBGAN) and optimizes the training process to generate high-quality surface defect samples. LMBGAN generates defect images and layer masks using the defect image decoder and layer mask decoder with the Pixel Shuffle operation. Inspired by the layer mask in computer painting, LMBGAN adopts the input image as the base layer and blends the defect foreground through the layer mask, giving it the ability to focus more on generating upper-layer defect images and reducing unnecessary background changes. LMBGAN additionally introduces adaptive discriminator augmentation and non-saturating logistic loss to promote model convergence under small datasets, effectively alleviating the problem of GAN training difficulties with limited data. The experiment results show that the proposed method can generate high-quality and diverse defect image samples through easily accessible normal samples, thus reducing the difficulty of obtaining rare defect image samples. © 2023 Copyright held by the owner/author(s).

关键词： Generative adversarial networks

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A Model Reference Adaptive controller with Feedforward Decoupling for Active Magnetic Bearing Rotor System 4

A Model Reference Adaptive Controller with Feedforward Decou...

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4th IEEE Advanced Information Technology, Electronic and Automation control Conference, IAEAC 2019

作者： Yi, Jian Ren, Gui-Ping Zhang, Hai-Tao Wu, Yue Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Wuhan430074 China

ISBN: (纸本)9781728119076

Active magnetic bearing (AMB) rotor system is widely applied in the industry for its remarkable advantages. However, it is a typical open-loop unstable mechatronics system suffering from nonlinear and couple characteristic. In this paper, the feedforward decoupling method is used to deal with the couple relationship of different axes. And the model reference adaptive control (MRAC) method is applied to improve the control performance and robustness and overcome the uncertainties. This control method makes the system output reach to the reference model by the designed adaptive law. Simulation results illustrate the effectiveness of the proposed scheme. © 2019 IEEE.

关键词： Model reference adaptive control

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Aero-thermal radiation correction via multi-scale bias field estimation 3

Aero-thermal radiation correction via multi-scale bias field...

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3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015

作者： Li, Lerenhan Yan, Luxin Sang, Nong Gao, Changxin Hu, Jing Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781479961009

In this paper, a multi-scale bias field estimation is proposed to carry out the aero-thermal radiation correction. The bias field is estimated at scales from coarse to fine by an alternative minimization, after which, the degraded image is restored via subtraction. In the minimization, Tiknov regularization is employed to constrain the smoothness of bias field while Total Variation (TV) is adopted to preserve the details and structures of the latent image. Besides, Split Bregman iteration is introduced to conquer the difficulty in the non-smooth problem when resolving the minimization. Compared with conventional approaches, experiments verified that the proposed method contributes to the rapidness and precision of the algorithm. © 2015 IEEE.

关键词： Iterative methods

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DeNet: An explicit distance ensemble model for person re-identification 3

DeNet: An explicit distance ensemble model for person re-ide...

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3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015

作者： Wang, Jin Gao, Changxin Hu, Jing Sang, Nong Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781479961009

In this paper, we address the problem of person reidentification (re-id), which remains to be challenging due to view point changes, pose variations, different camera settings, etc. Different from common methods that concatenate descriptors extracted from different support regions and feature channels directly as a long vector, we encode the importance of different feature channels and support regions explicitly and propose a two-layer distance ensemble model called DeNet to measure the similarity between two images. The first layer of DeNet combines distances of different support regions while the second layer weights different feature channels. Weight parameters of DeNet are learnt under the large margin framework with the goal of maximizing the difference between distances of positive and negative matching pairs. Our method achieves very competitive results on the widely used VIPeR and PRID 450S datasets. © 2015 IEEE.

关键词： Computers

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The assessment of EEG in patients with spinal cord injury to movements

The assessment of EEG in patients with spinal cord injury to...

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3rd International Symposium on intelligent Information Technology Application Workshops, IITAW 2009

作者： Li, Wei Huang, Yue Xu, Jiang Chen, Xi Wang, Xiaojun Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780769538600

Electroencephalography (EEG) is widely used in the field of neural engineering. EEG signals can describe the brain activities while the subjects with para/tetraplegia perform movement with their limbs. This paper reviews the research on the design of experiment, the different frequency bands of EEG signals and the data processing methods of EEG. According to the analysis of the previous studies, it has been concluded that EEG signal of alpha and beta frequency bands is of special significance for analyzing the brain activity of subjects with SCI during movements. And EEG signals also can be used for BCI with application in rehabilitation engineering. © 2009 IEEE.

关键词： Electroencephalography

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