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2012 International Conference on Modelling, Identification and control, ICMIC 2012

作者： Wu, Jun Wang, Yongji Huang, Jian Xing, Kexin Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China College of Information Engineering Zhejiang University of Technology Hangzhou Zhejiang 310032 China

ISBN: (纸本)9780956715715

Pneumatic Muscle (PM) has the advantages of cheapness, light weight, compliance, safe and high power/weight. It is suitable for rehabilitation engineering. To minimize the number of PM for driving a single joint of rehabilitation, a new PM-TS actuator comprising a PM and a Torsion Spring (TS) is proposed. Unlike the traditional agonist/antagonist PM actuator, the PM is arranged in appropriate place as agonist and the torsion spring provides opposing torque as antagonist in the proposed actuator. The dynamic model of a 1-DOF (Degree of Freedom) rehabilitation robotic arm is derived considering the PM-TS actuator. To realize high accurate trajectory tracking control of the robotic arm, an Artificial Bee Colony (ABC) algorithm based Auto-Disturbance Rejection control (ADRC) is proposed, where ABC is employed to optimize the control parameters of ADRC. Simulation results demonstrate the validity of PM-TS actuator, and verify that the ABC based ADRC has satisfactory performance. © 2012 Huazhong Univ of Sci & Tec.

关键词： Optimization

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Frequency Information Matters for image Matting 1

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7th Asian Conference on Pattern Recognition, ACPR 2023

作者： Luo, Rongsheng Wei, Rukai Gao, Changxin Sang, Nong Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Wuhan National Laboratory For Optoelectronics Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9783031476341

ISBN: (纸本)9783031476334

image matting aims to estimate the opacity of foreground objects in order to accurately extract them from the background. Existing methods are only concerned with RGB features to obtain alpha mattes, limiting the perception of local tiny details. To address this issue, we introduce frequency information as an auxiliary clue to accurately distinguish foreground boundaries and propose the Frequency Matting Network (FMN). Specifically, we deploy a Frequency Boosting Module (FBM) in addition to the Discrete Cosine Transform (DCT) to extract frequency information from input images. The proposed FBM is a learnable component that empowers the model to adapt to complex scenarios. Furthermore, we design a Domain Aggregation Module (DAM) to effectively fuse frequency features with RGB features. With the assistance of frequency clues, our proposed FMN achieves significant improvements in matting accuracy and visual quality compared with state-of-the-art methods. Extensive experiments on Composition-1k and Distinctions-646 datasets demonstrate the superiority of introducing frequency information for image matting. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Discrete cosine transforms

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Detection of billet character in complex production line scene

Detection of billet character in complex production line sce...

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2012 3rd International Conference on Digital Manufacturing and Automation, ICDMA 2012

作者： Hong, Hanyu Yu, Zhejun Zhang, Xiuhua Laboratory for Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430205 China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780769547725

Character information is hard to detect in billet scene images by CCD camera. In this paper, we present a method for detection of billet characters from measurements of recursive segmented image. This recursive segmented method can be used in a wide variety of billet scenes. According to high temperature and complex scene in the rolling line, we use an effective clustering and projection characteristics to determine the terminal condition of recursive segmentation. Then we can label character candidate regions in turn by this effective characteristics, and select the regions we want to achieve. The experiments show that this method makes full use of the characteristics of region and clustering. It can improve the quality of detection, and the detection result meets the need of practical application. © 2012 IEEE.

关键词： CCD cameras

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Learning Probabilistic Coordinate Fields for Robust Correspondences

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2023年第10期45卷 12004-12021页

作者： Zhao, Weiyue Lu, Hao Ye, Xinyi Cao, Zhiguo Li, Xin Huazhong University of Science and Technology The Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Wuhan430074 China West Virginia University The Lane Department of Computer Science and Electrical Engineering MorgantownWV26506-6109 United States

We introduce Probabilistic Coordinate Fields (PCFs), a novel geometric-invariant coordinate representation for image correspondence problems. In contrast to standard Cartesian coordinates, PCFs encode coordinates in correspondence-specific barycentric coordinate systems (BCS) with affine invariance. To know when and where to trust the encoded coordinates, we implement PCFs in a probabilistic network termed PCF-Net, which parameterizes the distribution of coordinate fields as Gaussian mixture models. By jointly optimizing coordinate fields and their confidence conditioned on dense flows, PCF-Net can work with various feature descriptors when quantifying the reliability of PCFs by confidence maps. An interesting observation of this work is that the learned confidence map converges to geometrically coherent and semantically consistent regions, which facilitates robust coordinate representation. By delivering the confident coordinates to keypoint/feature descriptors, we show that PCF-Net can be used as a plug-in to existing correspondence-dependent approaches. Extensive experiments on both indoor and outdoor datasets suggest that accurate geometric invariant coordinates help to achieve the state of the art in several correspondence problems, such as sparse feature matching, dense image registration, camera pose estimation, and consistency filtering. Further, the interpretable confidence map predicted by PCF-Net can also be leveraged to other novel applications from texture transfer to multi-homography classification. © 1979-2012 IEEE.

关键词： image registration

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A novel target tracking approach based on ORB used in micromanipulation system

A novel target tracking approach based on ORB used in microm...

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2012 International Conference on Modelling, Identification and control, ICMIC 2012

作者： Zuo, Lei Huang, Xinhan Zuo, Wen Key Laboratory of Image Processing and Intelligent Control of Education Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China College of Electronical Engineering Naval University of Engineering Wuhan 430033 China

ISBN: (纸本)9780956715715

Micromanipulation robot is a system which often does some precise manipulations in micro scale space, such as centimeter or millimeter level space, in which micro visual servo system plays a very important role. In visual servo system, it's difficult to give consideration to two or more things such as location accuracy and real-time property at the same time. In this paper, we introduced a novel approach which suited our system very well and could meet both of the above requirements. It was called ORB, a novel feature extracting method which outperformed many current excellent methods such as SIFT and SURF. © 2012 Huazhong Univ of Sci & Tec.

关键词： Target tracking

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Incremental feedback learning methods for voice recognition based on DTW

Incremental feedback learning methods for voice recognition ...

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2012 International Conference on Modelling, Identification and control, ICMIC 2012

作者： Chen, Xiaoxia Huang, Jian Wang, Yongji Tao, Chunjing Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Technology Huazhong University of Science and Technology Wuhan China R and D Department National Research Center for Rehabilitation Technical Aids Beijing China

ISBN: (纸本)9780956715715

A Dynamic Time Warping (DTW) based voice recognition approach and its template training problem are discussed in this paper. In order to achieve better recognition accuracies, we proposed two kinds of incremental feedback learning methods for DTW-based voice recognition, including the variable gain coefficient (VGC) based method and the time warping average (TWA) based method. Compared with the non-feedback recognition system, the proposed methods are easy to implement and more robust to noise. A number of comparison experiments are performed to demonstrate the effectiveness of the proposed method. It is also shown that the VGC-based method, whose implementation is easy, achieves significantly better performance than conventional batch template training method without feedback learning. © 2012 Huazhong Univ of Sci & Tec.

关键词： Speech recognition

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WDNet: A Water Depth Perception Network with Global Information 42

WDNet: A Water Depth Perception Network with Global Informat...

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42nd Chinese control Conference, CCC 2023

作者： Huang, Zhihui Tang, Yifeng Tang, Chuancong Xu, Yifan Luo, Chuanshang Liu, Bin Zhang, Hai-Tao School of Artificial Intelligence and Automation The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

Deep perception of the unmanned surface vehicle's surroundings is an inaccessible part of its fully autonomous navigation mission. The existing methods, whether based on traditional stereo matching or deep learning, do not fully consider the characteristics of water environment, resulting in severe error depths in weak textures (sky, calm lake) and water reflections regions, that increases the risk of running aground or collision. What is worse that there is not a public dataset for depth estimation in the water environment. Therefore, this work proposes a self-supervised model for depth estimation named Water Depth Perception Network (WDNet) to address these problems. The decoder of this network has a wider receptive field and can effectively handle the depth error in the weak texture region. Besides, the WDNet is trained with a novel and effective loss function which assist the network to reduce errors in sky and water region, and some indexes are proposed to evaluate the model's performances in sky and water region. Finally, our proposed WDNet achieves a 0.1056 absolute relative error in ranging, the average number of error pixels in the sky area drops from 15803.87 to 580.91, which only accounted for 0.29% of the image, and the error in water region drops from 51.04 to 6.75, all of them are superior to the performance of baseline model. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Errors

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Contrast-modulated nonlinear diffusion for X-ray angiogram images

Contrast-modulated nonlinear diffusion for X-ray angiogram i...

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2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005

作者： Li, Baopu Sang, Nong Cao, Zhiguo Department of Electronic Engineering Chinese University of Hong Kong Shatin N.T. Hong Kong Key Laboratory Ministry of Education for Image Processing and Intelligent Control Wuhan China

ISBN: (纸本)0780387406

In this paper, we present a new method for X-ray angiogram images enhancement using a contrast-modulated nonlinear diffusion. The original nonlinear diffusion is gradient driven, which leads into much dependence on the accurate estimation of the edge. However, it is very difficult to get the accurate estimation of edges for X-ray angiogram images, which are characterized with complex background. So it is necessary to do some improvements to this model. By designing a new concept of contrast space according to the characteristics of these images, we change the original nonlinear diffusion into contrast-modulated nonlinear diffusion. Compared with the traditional method, this new approach is proved to have a better performance of enhancement. © 2005 IEEE.

关键词： Medical imaging

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Dynamic Graph Dismantling with Reinforcement Supervised Learning 42

Dynamic Graph Dismantling with Reinforcement Supervised Lear...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Yumei Tang, Chuancong Zhang, Hai-Tao School of Artificial Intelligence and Automation Huazhong University of Science and Technology The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

There are always some 'key' nodes in a big complex network, which can joint the most connected subgraphs. How to identify these nodes, finding a minimum set of nodes to attack for reducing the size of residual network's Largest Connected Component(LCC) to break up the original network, has become a research hotspot. Therefore, a method for determining the 'key' nodes based on reinforcement learning framework and supervised learning model is proposed. This algorithm can not only utilize the dynamic exploration ability of reinforcement learning to collect a rich training dataset, but also take advantage of the characteristics that supervised learning is adaptive and has strong generalization ability to possess high efficiency and strong robustness. In order to further improve the algorithm's performance, ϵ-greedy mechanism is used to explore more network states. The experiment results show that given the same fraction of removed nodes, our algorithm can make the residual LCC smaller in various networks which is superior to the state-of-the-art algorithms in terms of effectiveness and generalization. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Complex networks

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Uniform Solution to QSAT by P Systems with Proteins

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Chinese Journal of Electronics 2023年第4期21卷 667-672页

作者： Chun LU Xiaolong SHI Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

P systems are distributed parallel computing models in the area of membrane computing, which are inspired by the structure and the functioning of living cells, as well as the organization of cells in tissues, organs, and other higher order structures. P systems with proteins on membranes are a class of P systems, which have proved to be very efficient computing devices. Specifically, it was known that the Quantified satisfiability problem (QSAT) of a Boolean formula can be solved by a semi-uniform family of P systems with proteins on membranes and with membrane division. However, it remains open whether a uniform families of P systems with proteins on membranes can solve in polynomial time exactly the class of problems PSPACE. In this work, we present a uniform solution to QSAT problem by P systems with proteins on membranes in a linear time with respect to both the number $n$ of Boolean variables and the number $m$ of clauses of the instance, which answers the above open problem.

关键词： Proteins image processing Computational modeling Organizations Parallel processing intelligent control

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