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12th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2012

作者： Gou, Gaopeng Huang, Di Wang, Yunhong Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Beihang University Beijing China

ISBN: (纸本)9783642326943

Video-based face clustering is a very important issue in face analysis. In this paper, a framework for video-based face clustering is proposed. The framework contains two steps. First, faces are detected from videos and divided into subgroups using temporal continuity information and SIFT (Scale Invariant Feature Transform) features. Second, the typical samples are selected from these subgroups in order to remove some non-typical faces. A similarity matrix is then constructed using these typical samples in the subgroups. The similarity matrix is further processed by our method to generate the face clustering results of that video. Our algorithm is validated using the SPEVI datasets. The experiments demonstrated promising results from our algorithm. © 2012 Springer-Verlag.

关键词： Clustering algorithms

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The design and implementation of a Chinese financial invoice recognition system

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Journal of Quantitative Linguistics 2002年第1期9卷 19-33页

作者： Ming, Delie Liu, Jian Tian, Jinwen State Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan Hubei Province 430074 China

This paper designs and implements a financial invoice recognition system based on the features of the Chinese financial invoice. By using the linear whole block moving method in each vertical segment, a new fast algorithm is put forth to detect and rectify the slant image. To distinguish the different form types (the foundation necessary for locating the form fields, filtering the form lines, etc.), several representative form features are discussed and an invoice-type features library is built by using a semi-automatic machine study method. On the basis of the recognized invoice type, real invoice form is re-oriented against the corresponding blank form according to the invoice type feature, solving the problem of adhesion of characters and form lines, as well as the problem of character segmentation and recognition. Based on the Chinese financial invoice image feature, a mutual rectification mechanism founded on the recognition results of Chinese financial characters and Arabic numerals is put forward to raise the recognition rate. Finally, the experimental results and conclusions are presented. © Swets & Zeitlinger.

关键词： LINGUISTICS WORD recognition -- Software

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Semi-supervised segmentation of multispectral remote sensing image based on spectral clustering

Semi-supervised segmentation of multispectral remote sensing...

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

作者： Zhang, Xiangrong Wang, Ting Jiao, Licheng Yang, Chun Key Laboratory of Intelligent Perception and Image Understanding Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478054

In this paper, a new multi-spectral remote sensing image segmentation method based on multi-parameter semi-supervised spectral clustering (STS 3C) is proposed. Two types of instance-level constraints: must-link and cannot-link are incorporated into spectral cluster to construct semi-supervised spectral clustering in which the self-tuning parameter is applied to avoid the selection of the scaling parameter. Further, when STS 3C is applied to multi-spectral remote sensing image segmentation, the uniform sampling technique combined with nearest neighbor rule is used to reduce the computation complexity. Segmentation results show that STS 3C outperforms the semi-supervised spectral clustering with fixed parameter and the well-known clustering methods including k-means and FCM in multi-spectral remote sensing image segmentation. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image segmentation

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Towards independent color space selection for human skin detection

Towards independent color space selection for human skin det...

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13th Pacific-Rim Conference on Multimedia, PCM 2012

作者： Xu, Tao Wang, Yunhong Zhang, Zhaoxiang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Beihang University Beijing China

ISBN: (纸本)9783642347771

Skin color detection plays an important role in video based applications. Without considering the selection of suitable color space, a novel skin color detection method is proposed based on the flexible neural tree, which can identify the important components of color spaces automatically. With large training data sets, our method builds a flexible neural tree structure and optimizes its parameters using Genetic Programming and Particle Swarm Optimization algorithms. In experiments, features comprised of all channels extracted from RGB, YCbCr and HSV color spaces are used for the constructing and evaluating of the novel skin color model, in which six most important components, i.e., R, G, B, Y, Cr and S are selected for testing. Furthermore, our method achieves higher accuracy and lower false positive rate than state of the art methods on Compaq and ECU data set. © 2012 Springer-Verlag.

关键词： Genetic programming

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Stability Analysis and controller Design of Positive Linear Systems Subject to Actuator Saturation

Stability Analysis and Controller Design of Positive Linear ...

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第三十二届中国控制会议

作者： ZHANG Jishi Wu Yan WANG Yanwu GAO Zhonghu School of Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan Institute of Marine Electric Propulsion CSIC

ISBN: (纸本)9781479900305

This paper addresses the stability and stabilization problems for a class of positive linear systems in the presence of saturating *** objective is to give conditions of the stability,and design state feedback control laws such that the closed-loop systems is asymptotically stable and positive at the origin with a large domain of *** sufficient conditions for stabilization and positivity are derived via the Lyapunov functions method and convex analysis in both the continuous-time and the discrete-time cases,*** state feedback controller design and the estimation of domain of attraction are presented by solving a convex optimization problem with LMIs constraints.A numerical example is given to show the effectiveness of the proposed methods.

关键词： Actuator Saturation Stability Analysis Positive System Domain of Attraction

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Cross-user Gesture Recognition Based on Deep Domain Adaptation Networks 43

Cross-user Gesture Recognition Based on Deep Domain Adaptati...

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43rd Chinese control Conference, CCC 2024

作者： Fu, Zhongzheng He, Xinrun Wang, Haoyuan Chen, Xingjian Li, Yixuan Huang, Jian Huazhong University of Science and Technology Ministry of Education Key Laboratory of Image Processing and Intelligent Control Hubei Key Laboratory of Brain-inspired Intelligent Systems School of Artificial Intelligence and Automation Wuhan430074 China

ISBN: (纸本)9789887581581

This study introduces an innovative approach for gesture recognition in smart wearable devices using a deep domain adaptation model, focusing on the challenges posed by heterogeneous user environments and the need for precise, adaptable, and personalized gesture recognition systems. Traditional methods based on machine learning and deep learning techniques, while effective, struggle with the variance in data distribution among different users, leading to accuracy challenges. To address this, the study proposes the Domain Kernel-Alignment Adaptation Network (DKAN) model, utilizing a new Kernel-Aligned Multi-kernel Maximum Mean Discrepancy (KAMMD) method within deep networks. By calculating kernel alignments between source and target domains and adjusting weights of Gaussian kernels accordingly, DKAN emphasizes features conducive to transfer learning, enabling more accurate cross-user gesture recognition. The model achieves a significant average accuracy of 97.3% across 21 gestures, highlighting its potential in practical applications. This advancement addresses challenges in traditional gesture recognition methods and sets a new direction for future research in smart wearable technology. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Adversarial machine learning

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SAR image classification based on correlation of directional features in frequency domain

SAR image classification based on correlation of directional...

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

作者： Zhong, Hua Yang, Xiaoming Jiao, Licheng Institution of Intelligent Information Processing Key Laboratory of Intelligent Perception and Image Understanding Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478078

A new SAR image classification method is proposed based on the remarkable correlation of feature channels, which are obtained by dividing the Fourier plane into sectors according to the frequency and direction. Compared with other feature correlation based methods in wavelet and Contourlet domain, our method operates directly in the Fourier plane, which is more robust with regard to images size and more flexible in the capture of frequency and directional information. Moreover, the use of FFT transform is computationally more attractive. Experimental results on the Brodatz textures and SAR images demonstrate the effectiveness and efficiency of the proposed method. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Classification (of information)

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Demand-Side Frequency control in Power Network Based on Multi-Agent Deep Reinforcement Learning 5

Demand-Side Frequency Control in Power Network Based on Mult...

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5th International Conference on Industrial Artificial Intelligence, IAI 2023

作者： Liu, Xianggang Liu, Zhi-Wei Chi, Ming Zhang, Yifan Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education College of Artificial Intelligence and Automation Wuhan China

ISBN: (纸本)9798350325294

The integration of renewable energy sources into the power grid has led to new challenges in maintaining the stability of the system frequency. This paper proposes a novel approach to address the Optimal Demand Side Frequency control (ODFC) problem using Multi-Agent Deep Deterministic Policy Gradient (MADDPG) method. The proposed method models the ODFC problem as a Markov game, with centralized training based on multi-agent cooperative self-learning and associative storage service. In the decentralized execution stage, each agent independently outputs control actions to the controlled plant using local observations. Numerical simulations show that the proposed method effectively addresses the ODFC problem with superior performance compared to traditional methods. © 2023 IEEE.

关键词： Numerical methods

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A traffic flow detection system combining optical flow and shadow removal

A traffic flow detection system combining optical flow and s...

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2011 3rd Chinese Conference on intelligent Visual Surveillance, IVS 2011

作者： Zhang, Zhaoxiang Hou, Yuqing Wang, Yunhong Qin, Jie Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Beihang University Beijing China

ISBN: (纸本)9781457718311

Traffic flow detection plays an important role in intelligent Transportation Systems(ITS). Video based traffic flow detection system is the most widely used strategy in ITS. Under this circumstance, we design and implement a video based traffic flow detection system which is called MyTD in this paper. MyTD takes advantages of both shadow removal and optical flow algorithms. Firstly, we introduce the current development of ITS and focus on the video based traffic detection technology, which is the key to ITS. Secondly, a shadow removal algorithm combining information in both RGB and HSV color spaces is proposed. Thirdly, based on the Iterative Pyramidal LK Optical Flow Algorithm, a vehicle tracking function is realized by OpenCV, as well as a Connected Components Labeling function and the vehicle counting function. Finally, MyTD is implemented and tested based on the algorithm presented above. Experimental results show the outstanding performance of our method comparing with traditional optical flow algorithms. © 2011 IEEE.

关键词： Optical flows

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Graph-based scale-aware network for human parsing 1

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2nd Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2019

作者： Yang, Beibei Yu, Changqian Liu, Jiahui Gao, Changxin Sang, Nong Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9783030317232

ISBN: (纸本)9783030317225

Recent work has made considerable progress in exploring contextual information for human parsing with the Fully Convolutional Network framework. However, there still exist two challenges: (1) inherent relative relationships between parts;(2) scale variation of human parts. To tackle both problems, we propose a Graph-Based Scale-Aware Network for human parsing. First, we embed a Graph-Based Part Reasoning Layer into the backbone network to reason the relative relationship between human parts. Then we construct a Scale-Aware Context Embedding Layer, which consists of two branches to capture scale-specific contextual information, with different receptive fields and scale-specific supervisions. In addition, we adopt an edge supervision to further improve the performance. Extensive experimental evaluations demonstrate that the proposed model performs favorably against the state-of-the-art human parsing methods. More specifically, our algorithm achieves 53.32% (mIoU) on the LIP dataset. © Springer Nature Switzerland AG 2019.

关键词： Embeddings

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