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Control, Electronics and Computer Technology (ICCECT), IEEE International Conference on

作者： Shaoqi Xia Hua Huang Qishen Li Yifan He Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition School of Information Engineering Nanchang Hangkong University Nanchang China School of Information Engineering Nanchang Hangkong University Nanchang China Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition School of Software Nanchang Hangkong University Nanchang China

Semantic segmentation is one of the most important research directions in the field of computer vision, and has a wide range of applications for autonomous driving, medical imaging, intelligent security, etc. Unsupervised domain adaptation is the mainstream research topic in recent years, which can use a large number of labeled source samples to complete the segmentation task in target domain without labeled target samples. In this paper, we propose a prototype-guided unsupervised domain adaptation for semantic segmentation based on ProDA model. Due to lacking of labeled target samples and the prior probability, a prototype distance loss based on target domain is proposed to optimize the distribution of features by measuring the distance between features and the updated prototype and designing an adaptive threshold strategy. Meanwhile, a smoothing loss is proposed to alleviate the impact of source samples on our model and improve the prediction performance of the network. By conducting experiments on the GTA5 to Cityscapes scenarios, the results show that compared with the original model, the loss optimization improves mIoU by1.52.

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A fusion algorithm of remote sensing image based on discrete wavelet packet

A fusion algorithm of remote sensing image based on discrete...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Hai-Hui Wang Jia-Xiong Peng Wei Wu State Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)0780378652

image fusion refers to the techniques that integrate complementary information from multiple image sensor data such that the new images are more suitable for the purpose of human visual perception and the compute processing tasks. In this paper, a new image fusion algorithm based on wavelet packet transform to fuse multisensor images is presented. Discrete wavelet transform (DWT) can offer a more precise way for image analysis, than other multi-resolution analysis. It decomposes an image into low frequency band and high frequency band in different level, and it can also be reconstructed gradually in different level. But this method only decomposes low frequency band in a higher scale, so that it omits some useful details of the images. In this paper, we present a new image fusion algorithm. In the algorithm, we use discrete wavelet packet transform (DWPT) to decompose and reconstruct the images. When images are merged in wavelet packet space, different frequency ranges are processed differently. It can merge information from original images adequately and improve abilities of information analysis and feature extraction. This image fusion is performed at the pixel level. In this fusion algorithm, a feature-based fusion rule is used to combine original subimages and to form a pyramid for the fused image. Through merging remote sensing images from multi-sensor to a same object by applying method of wavelet packet analysis, we have obtained a fused picture. In this paper, mutual information is employed as a means of objective assessing image fusion performance. The experiment results show that this fusion algorithm, based on wavelet packet transform, is an effective approach in image fusion area.

关键词： Remote sensing Discrete wavelet transforms Wavelet packets image fusion Frequency image analysis Wavelet analysis image reconstruction image sensors Humans

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Software quality prediction using Affinity Propagation algorithm

Software quality prediction using Affinity Propagation algor...

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International Joint Conference on Neural Networks (IJCNN)

作者： Bingbing Yang Qian Yin Shengyong Xu Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China Laboratory of Computer Science Institute of Software Chinese Academy and Sciences Beijing China

Software metrics are collected at various phases of the software development process. These metrics contain the information of the software and can be used to predict software quality in the early stage of software life cycle. Intelligent computing techniques such as data mining can be applied in the study of software quality by analyzing software metrics. Clustering analysis, which can be considered as one of the data mining techniques, is adopted to build the software quality prediction models in the early period of software testing. In this paper, a new clustering method called Affinity Propagation is investigated for the analysis of two software metric datasets extracted from real-world software projects. Meanwhile, K-Means clustering method is also applied for comparison. The numerical experiment results show that the Affinity Propagation algorithm can be applied well in software quality prediction in the very early stage, and it is more effective on reducing Type II error.

关键词： Software Software quality Clustering methods Clustering algorithms Software metrics Testing Software algorithms

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A Control Method for Electric Cylinder Based on Three-Order ADRC

A Control Method for Electric Cylinder Based on Three-Order ...

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WRC Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Zhifan Jiang Zhihua Chen Lijun Tong Jiale Huang Yufei Che Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition and MOE Key Lab of Nondestructive Testing Technology Nanchang Hangkong University Nanchang

ISBN: (数字)9798331506100

ISBN: (纸本)9798331506117

As an executive component of robots, the precise control of electric cylinders is crucial for achieving accurate control of robots. This article proposes a position closed-loop electric cylinder control method based on three-orders active disturbance rejection control (ADRC). Firstly, model the electric cylinder system and determine its transfer function. Secondly, PID controllers and ADRC controllers were designed separately, and their stability was verified through the Routh criterion and Lyapunov method, respectively. Finally, the control effects of PID and ADRC were compared through three sets of experiments. The results show that compared to PID, ADRC is less affected by the increase in input signal frequency, has stronger anti-interference ability, and can effectively resist the influence of internal uncertainty.

关键词： Robust control Automatic frequency control PI control Uncertainty Stability criteria Transfer functions Resists PD control Robots Lyapunov methods

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Adaptive regularization deconvolution extraction algorithm for spectral signal processing

Adaptive regularization deconvolution extraction algorithm f...

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IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA)

作者： Jian Yu Ping Guo A-li Luo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China National Astronomical Observatories Chinese Academy of Sciences Beijing China

Deconvolution is known as an ill-posed problem. In order to solve such a problem, a regularization method is needed to constrain the solution space and find a plausible and stable solution. In practice, it is very computation intensive when using cross-validation method to select the regularization parameter. In this paper, we present an adaptive regularization method to find the optimal regularization parameter value and represent the trade-off between model fitness of the data and the smoothness of the extracted signal. Spectral signal extraction experimental results demonstrate that the time complexity the proposed method is much lower than the one without adaptive regularization and is convenient for users also. And quantitative performance analysis show that the proposed intelligent approach performs better than that of current deconvolution extraction method and other extraction method used in the Large Area Multi-Objects Fiber Spectroscopy Telescope spectral signal processing pipeline.

关键词： Deconvolution Charge coupled devices Equations Apertures Convolution Mathematical model Sparse matrices

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A parallel coordinative visual model-the plate parallel retrieval model (PPRM)

A parallel coordinative visual model-the plate parallel retr...

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International Conference on Signal processing Proceedings (ICSP)

作者： Wang Tianzhen Li Zhou Chang Suwen Wu Zhongyi Du ping National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China Image Processing Laboratory Wuhan Automotive Polytechnic University Wuhan China

In this paper, a parallel coordinative visual model-the revised plate parallel retrieval model (Wang Tianzhen et al, 1994) is presented based on the analysis of the global effect of Chinese characters and the recent neurobiological research on the function of neuroglia in learning and memory. The theory assumes that visual neurons possess the function of memory and retrieval in addition to the commonly recognised function of signal transformation. It supposes all the pixels in the array of a Chinese character are encoded, stored and retrieved simultaneously and synchronously by each neuron separately. In the model, neuroglia cells play an important role in the integration of the visual signal. The model cannot only satisfactorily explain both the global effect and strokes effect, but can also explain the implicit memory of Chinese characters as well. We have experimented on an SIMD array processor to prove the viability of the PPR algorithm. The results are satisfactory. The model can be extended to general shape vision with some conditions.

关键词： Neurons Character recognition image retrieval image processing Frequency Visual system Information retrieval Centralized control Biomembranes Switches

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A robust approach to the detection and tracking of small targets with low contrast

A robust approach to the detection and tracking of small tar...

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IEEE International Workshop on VLSI Design and Video Technology, IWVDVT

作者： Xinyu Wang Guilin Zhang Ying Chu State Key Laboratory for Image Processing and lntelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)0780390059

An effective approach to the detection and tracking of small moving targets with low contrast is proposed. In our application, small moving targets are detected and tracked in a low quality video sequence captured from an airborne platform. The detection and tracking system includes three modules. First, the global motion parameters are estimated using fast least trimmed squares (FAST-ITS) regression and hierarchical processing. Once the global motion is robustly estimated, relatively stationary background can be eliminated almost completely through image warping. Then a motion-based fast target detector selects candidate pixels of the moving targets with motions statistically different from that of the background, and a particle filtering tracker examines the temporal consistency of targets to identify them and update their states. Information in the system flows in a closed loop form, in which the tracker instructs the detector where to look for a target, and the detector returns what it has found. Experimental results prove that the proposed method can reliably and effectively detect and track the real small moving target in real-time even if there is strong clutter influence.

关键词： Robustness Target tracking Detectors Motion estimation Video sequences Parameter estimation Motion detection Filtering Particle tracking Tracking loops

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High Performance Reconfigurable Hardware System for real-time image processing

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Journal of Systems Engineering and Electronics 2005年第3期000卷 502-509页

作者： Zhao Guangzhou Zhang Tianxu Wang Yuehuan Cao Zhiguo Zuo Zhengrong State Key Laboratory for Image Processing and Intelligent Control，Inst.for Pattern Recognition and Artificial Intelligence，Huazhong Univ.of Science and Technology，Wuhan 430074，P.R.China

A novel reconfigurable hardware system which uses both multi-DSP and FPGA to attain high performance and real-time image processing are presented. The system structure and working principle of mainly processing multi-DSP board, extended multi-DSP board are analysed. The outstanding advantage is that the communication among different board components of this system is supported by high speed link ports & serial ports for increasing the system performance and computational power. Then the implementation of embedded real-time operating systems (RTOS) by us is discussed in detail. In this system, we adopt two kinds of parallel structures controlled by RTOS for parallel processing of algorithms. The experimental results show that exploitive period of the system is short, and maintenance *** it is suitable for real-time image processing and can get satisfactory effect of image recognition.

关键词： rmulti-DSP field programmable gate arrays real-time image processing real time operating systems paralld structure

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DAmageNet: A universal adversarial dataset

arXiv

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arXiv 2019年

作者： Chen, Sizhe Huang, Xiaolin He, Zhengbao Sun, Chengjin Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University MOE Key Laboratory of System Control and Information Processing 800 Dongchuan Road Shanghai200240 China

It is now well known that deep neural networks (DNNs) are vulnerable to adversarial attack. Adversarial samples are similar to the clean ones, but are able to cheat the attacked DNN to produce incorrect predictions in high confidence. But most of the existing adversarial attacks have high success rate only when the information of the attacked DNN is well-known or could be estimated by massive queries. A promising way is to generate adversarial samples with high transferability. By this way, we generate 96020 transferable adversarial samples from original ones in imageNet. The average difference, measured by root means squared deviation, is only around 3.8 on average. However, the adversarial samples are misclassified by various models with an error rate up to 90%. Since the images are generated independently with the attacked DNNs, this is essentially zero-query adversarial attack. We call the dataset DAmageNet, which is the first universal adversarial dataset that beats many models trained in imageNet. By finding the drawbacks, DAmageNet could serve as a benchmark to study and improve robustness of DNNs. DAmageNet could be downloaded in http://***/Show/56/122 Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

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A new approach of color quantization based on ant colony clustering algorithm

A new approach of color quantization based on ant colony clu...

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International Conference on Information Technology: Coding and Computing (ITCC)

作者： Xinrong Hu Tianzhen Wang Dehua Li Institute for Pattern Recognition and Artificial Intelligence State Education Commission Laboratory Image Processing and Intelligence Control Huazhong University of Science and Technology Wuhan China Institute of Image Processing Wuhan University of Technology China

ISBN: (纸本)0769523153

Color quantization is wildly exploited for many applications especially in the fields of computer graphics and image processing. After studying the approaches of color clustering, a new approach based on ant colony clustering algorithm applied in color image quantization is proposed in the paper. According to the picking up-dropping theory, a promoted ant algorithm is applied to group colors into certain clusters in RGB space. It finishes color quantization after colors mapping of every pixel. Our experiment shows that the algorithm proposed in this paper has rather good performance with an excellent robustness, a less time consumption, and a simple realization.

关键词： Quantization Clustering algorithms Information technology

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