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2011 IEEE International conference on Intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

作者： Qi, Jian Ding, Mingyue Yuchi, Ming Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Life Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769546230

The data acquisition of 3D-Ultrasound includes array scan and mechanical scan, and the later one is more easy to realize. Currently, the traditional probe scanning mode is Front-end scanning. Under the above scanning mode, when it scans over the breast, 2D-Ultrasound probe slides through the surface of the patients' bodies, the image will be influenced strongly by the human *** this paper we propose a new scanning mode to solve the above problem: Back-End scan, the back end rotates while the front end contacts the patients' skin without slide. The device designed using dual stepper motors which are under the synchronization control. Experiment results show the effectiveness of the proposed device. © 2011 IEEE.

关键词： Scanning

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Blind noisy image separation based on a new robust independent component analysis network

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Chinese Optics Letters 2006年第10期4卷 573-575页

作者：纪建田铮 Department of Computer Science & Technology Northwestern Polytechnical University Xi'an 710072 Department of Applied Mathematics Northwestern Polytechnical UniversityXi'an 710072 Key Laboratory of Education Ministry for Image Processing and Intelligent ControlHuazhong University of Science & TechnologyWuhan 430074

The separation of noisy image is a very exciting area of research, especially when no prior information is available about the noisy image. In this paper, we propose a robust independent component analysis （ICA） network for separation images contaminated with high-level additive noise or outliers. We reduce the power of additive noise by adding outlier rejection rule in ICA. Extensive computer simulations confirm robustness and the excellent performance of the resulting algorithms.

关键词： Algorithms Computer simulation Independent component analysis

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Reliability on deep learning models: A comprehensive observation 6

Reliability on deep learning models: A comprehensive observa...

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6th International Symposium on System and Software Reliability, ISSSR 2020

作者： Zhang, Yuhong Xiao, Chunjing School of Artificial Intelligence and Big Data Key Laboratory of Grain Information Processing and Control Ministry of Education Zhengzhou China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China

ISBN: (纸本)9780738104973

This paper provides a comprehensive observation to examine the reliability of deep learning (DL) models. First, we will briefly introduce the essential background and kernel techniques in deep learning, such as downsampling and nonlinear discontinuity. Each of them may have some relation to the reliability of DL models. Then we discuss the inherent structural flaws of deep learning and the risk of unreliability that can result from it. Subsequently, we discuss various ways of generating adversarial samples that affect the DL model's reliability and corresponding preventive measures. Finally, we complete this observation by identifying current challenges and future trends for research. © 2020 IEEE.

关键词： Reliability

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Guest Editorial:Advances in Bio-inspired Heuristics for Computing

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CAAI Transactions on intelligence Technology 2019年第3期4卷 127-128页

作者： XINCHAO ZHAO MAOGUO GONG XINGQUAN ZUO LINQIANG PAN School of Science Beijing University of Posts and TelecommunicationsBeijing 100876PR China Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian UniversityXi’an 710071PR China School of Computer Science Beijing University of Posts and TelecommunicationsBeijing 100876PR China Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of AutomationHuazhong University of Science and TechnologyWuhan 430074PR China

Bio-inspired computing (BIC), short for biologically inspired computing, is a field of study that loosely knits together subfields related to the topics of connectionism, social behaviour and emergence. The field of bio-inspired computing brings together researchers from many disciplines, including biology, computer science, mathematics, physics and genetics.

关键词： Guest Editorial Advances Bio-inspired Heuristics Computing

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Fully Circuit Implementation of a two-layer Memristive Neural Network for Pattern Recognition 11

Fully Circuit Implementation of a two-layer Memristive Neura...

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11th International Conference on Information Science and Technology, ICIST 2021

作者： Li, Mian Wang, Xiaoping Chen, Zhanfei Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China

ISBN: (纸本)9781665412667

In this paper, a fully circuit implementation of Memristive Neural Network (MNN) is proposed. The forward calculation of the network is based on winner-take-all (WTA) mechanism. The weight updating is achieved through the difference of pre-spike and post-spike, which is more close to the biological weight adjustment mechanism. The network is implemented in a full circuit without additional control units. The designed circuit consists of four modules. The memristive crossbar array module with one-memristor (1M) unit structure can effectively calculate the vector-matrix multiplication with only one step. The switch S is replaced by the transistor in the designed leaky-integrate-and-fire (LIF) module, which can control the integration and leakage of the membrane voltage and realize the lateral inhibition between output neurons. Connecting the integrated monostable trigger and the difference circuit, the post-spike generating module can output the required post-spike. The signal switch module realizes the switching of signals connected to memristors by using voltage-controlled switches. The combination of two modules validly realizes weight updating. The functions of four modules are verified separately. We performed a simulation experiment of 5×3 pixels image classification based on the designed circuit in PSPICE. The circuit output results and the high classification accuracy prove the circuit can be effectively applied in pattern recognition. The noise experiment shows the robustness of the designed circuit. © 2021 IEEE.

关键词： image classification

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An overview of Hierarchical Temporal Memory: A new neocortex algorithm

An overview of Hierarchical Temporal Memory: A new neocortex...

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

作者： Chen, Xi Wang, Wei Li, Wei Institute of System Engineering Huazhong University of Science and Technology Education Ministry of China Wuhan Hubei 430074 China Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory Education Ministry of China China

ISBN: (纸本)9780956715715

The overview presents the development and application of Hierarchical Temporal Memory (HTM). HTM is a new machine learning method which was proposed by Jeff Hawkins in 2005. It is a biologically inspired cognitive method based on the principle of how human brain works. The method invites hierarchical structure and proposes a memory-prediction framework, thus making it able to predict what will happen in the near future. This overview mainly introduces the developing process of HTM, as well as its principle, characteristics, advantages and applications in vision, image processing and robots movement, some potential applications by using HTM, such as thinking process, are also put forward. © 2012 Huazhong Univ of Sci & Tec.

关键词： Forecasting

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Federated Multitask Learning for HyperFace

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial intelligence 2022年第5期3卷 788-797页

作者： Zhang, Chen Bai, Hang Zhang, Yonggang Niu, Xinyi Yu, Bin Gao, Yuan Xie, Yu Xidian University School of Computer Science and Technology Xi'an710071 China Shaanxi Province Science and Technology Resources Coordination Center Xi'an710071 China Xidian University Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education Xi'an710071 China Shanxi University Key Laboratory of Computational Intelligence and Chinese Information Processing Ministry of Education Taiyuan030006 China

Multitask learning (MTL) is a promising field in machine learning owing to its capability to improve the generalization performance of all tasks by sharing knowledge among the related tasks. MTL has attracted a large amount of attention in the multitask-related community. In recent years, with the rapid development of distributed machine learning, MTL in a distributed environment becomes a hot research topic. Although MTL can reap great fruit in a distributed environment, the sensitive information, such as photos and voice recordings of the owner, in distributed data may be leaked during training. Consequently, in the distributed settings, one prominent challenge of MTL is to prevent the disclosure of sensitive private data. In this article, we propose a novel approach, federated multitask learning (FMTL), which applies federated learning to MTL in a distributed environment in order to protect the MTL model from being leaked and to better optimize the utility of the MTL model. In FMTL, all the participants independently train their local models on their own dataset in parallel and only transmit their model updates to the central server for aggregation at every epoch. As a result, their learning accuracy is enhanced beyond what is achieved only on their own training data. In this manner, it can achieve the best tradeoff between the utility and privacy: participants not only preserve the privacy of their own data, but also benefit from the models of other participants. The experimental results on annotated facial landmarks in the wild (AFLW) and annotated faces in the wild (AFW) benchmark datasets verify the effectiveness of our framework. © 2020 IEEE.

关键词： Linearization

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A novel estimation strategy for the eye-in-hand depth-independent visual servoing

A novel estimation strategy for the eye-in-hand depth-indepe...

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2011 International Conference on Consumer Electronics, Communications and Networks, CECNet 2011

作者： Liang, Xinwu Huang, Xinhan Wang, Min Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Dept. of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China

ISBN: (纸本)9781612844572

As we know, a novel adaptive visual servoing strategy has been proposed for the control of robot manipulators with an eye-in-hand configuration, where an adaptive law is used to estimate the unknown parameters determined by the products of the unknown 3D coordinates and the unknown camera parameters. From a practical point of view, in this paper, we propose a novel strategy for the estimation of these two types of unknown parameters. The new strategy is very useful in that it can reduce the number of the unknown parameters to be estimated. To demonstrate the feasibility of the proposed method, preliminary simulation results based on a two-link planar robot manipulator are presented in this paper. © 2011 IEEE.

关键词： Parameter estimation

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Solving 0-1 planning problem based on self-assembly of dna tiles

Solving 0-1 planning problem based on self-assembly of dna t...

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作者： Huang, Yufang Cheng, Zhen Xu, Jin Shi, Xiaolong Zhou, Kang Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology 430074 Wuhan China Ministry of Education 10087 Beijing China

DNA tile self-assembly has been proved to enable programmable manipulation of biological systems as a tool of molecular computation. It is mainly based on the property that is the spontaneous self-ordering of substructure into superstructure driven by annealing of Watson-Crick base-pairing DNA sequences. We take full advantage of the superiority of DNA tile self-assembly to construct a molecular computing system that implements a solution for the 0-1 planning problem. This algorithm can independently and simultaneously yield the data pool, containing all possible solutions when all basic operation tiles are designed beforehand. Then we can use some advanced bio-chemistry techniques to select the optimization solutions of the 0-1 planning problem. Our work has shown that it is possible to work with an exponential number of components to solve NP-complete problems. The method proposed here also can reduce the number of laboratory steps required for computation so that it can improve the computation speed. Copyright © 2010 American Scientific Publishers. All rights reserved.

关键词： Self assembly

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3D model retrieval using density-based silhouette descriptor

3D model retrieval using density-based silhouette descriptor

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2nd International Conference on Pattern Recognition Applications and Methods, ICPRAM 2013

作者： Tang, Qi Yang, Xin Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

ISBN: (纸本)9789898565419

In this paper we present a new content-based retrieval descriptor, density-based silhouette descriptor (DBS). It characterizes a 3D object with multivariate probability functions of its 2D silhouette features. The new descriptor is computationally efficient and induces a permutation property that guarantees invariance at the matching stage. Also, it is insensitive to small shape perturbations and mesh resolution. The retrieval performance on several 3D databases shows that the DBS provides state-of-art discrimination over a broad and heterogeneous set of shape categories.

关键词： Probability density function

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