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Spectrum Sensing Based on Deep Learning Classification for Cognitive Radios

China Communications 2020年第2期17卷 138-148页

作者： Shilian Zheng Shichuan Chen Peihan Qi Huaji Zhou Xiaoniu Yang Science and Technology on Communication Information Security Control Laboratory Jiaxing 314033China State Key Laboratory of Integrated Service Networks Xidian UniversityXi’an 710071China Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education of ChinaXidian UniversityXi’an 710071China

Spectrum sensing is a key technology for cognitive *** present spectrum sensing as a classification problem and propose a sensing method based on deep learning *** normalize the received signal power to overcome the effects of noise power *** train the model with as many types of signals as possible as well as noise data to enable the trained network model to adapt to untrained new *** also use transfer learning strategies to improve the performance for real-world *** experiments are conducted to evaluate the performance of this *** simulation results show that the proposed method performs better than two traditional spectrum sensing methods,i.e.,maximum-minimum eigenvalue ratio-based method and frequency domain entropy-based *** addition,the experimental results of the new untrained signal types show that our method can adapt to the detection of these new ***,the real-world signal detection experiment results show that the detection performance can be further improved by transfer ***,experiments under colored noise show that our proposed method has superior detection performance under colored noise,while the traditional methods have a significant performance degradation,which further validate the superiority of our method.

关键词： spectrum sensing deep learning convolutional neural network cognitive radio spectrum management

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A Novel Small Dim Infrared Target Detecting Method based on Grayscale Merging and Connected Components Analysis

A Novel Small Dim Infrared Target Detecting Method based on ...

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2012 International Conference on Modelling,Identification and control(建模、辨别与控制国际会议 ICMIC 2012)

作者： Ying Zhang Min Wang Shaoqing Niu Key Laboratory of Image Processing and Intelligent Control of Education Department of Control Scienc Key Laboratory of Image Processing and IntelligentControl of Education Department of Control Science Key Laboratory of Image Processing andIntelligent Control of Education Department of Control Science

Target detecting algorithm in infrared image is drawing extensive attention both at home and abroad, expecially when the infrared images own complex backgrounds and low *** to make sure of the accuracy of infrared dim-small target detecting is the key point during the processing *** this paper, a novel region of interest detecting algorithm is proposed for aerial small dim infrared target with clutter *** from traditional region of interest extraction method, we extract region of interest based on the grayscale merging algorithm and connected components analysising ***, the infrared image is reconstructed by separating the grayscale into several interval sections, then binarization is used to segment the processed image according to estimate the threshold value using minimum error probability;finally, analysis and select the connected components, to sift the accurate connected domain which contain the *** validity of the proposed approach is demonstrated by experiment of infrared target region extraction.

关键词： Infrared small-dim target object detection connected component minimum error probability

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Background suppression based-on wavelet transformation to detect infrared target

Background suppression based-on wavelet transformation to de...

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International Conference on Machine Learning and Cybernetics, ICMLC 2005

作者： Sun, Y.U.-Qiu Tian, Jin-Wen Liu, Jian School of Information and Mathematics Yangtze University Jingzhou 434023 China State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China State Education Commission Key Laboratory for Image Processing and Intelligent Control Dept. of Electronic Information and Enginery Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)078039092X

Target detection and location in infrared clutter background is very important to infrared search and track system. Especially for small target detection in infrared image in background of sea and sky, there are no geometric and structure character to use. When targets such as ship and naval vessel sailing at long distance, they always appear around the sea-level line, and it is mixed with cloud and sea-wave clutter. It is difficult to segment and locate precisely. Background suppression based-on wavelet transformation is proposed in the paper. Wavelet decomposition makes it possible to analyze a signal both in time and frequency domains. In the paper infrared sea and key background images are processed. For their SNR is low and background is complex, using wavelet transformation decomposes an original image and extract approximate feature to reconstruct an image, which mainly includes background information. A new image will be obtained using background image subtracted from original image. There are mainly target and noise points left in the new image. By setting proper threshold, the target can be detected perfectly. At last, experiment results are given and show the method is practical. © 2005 IEEE.

关键词： Pattern recognition

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Analysis of memory property on the memristor based on the current and constant of integration

Analysis of memory property on the memristor based on the cu...

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2011 International Conference on Information Science and Technology, ICIST 2011

作者： Bao, Gang Shen, Yi Zeng, Zhigang Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hubei 430074 China Key Laboratory of Image Processing and Intelligent Control Education Ministry of China Wuhan Hubei 430074 China

ISBN: (纸本)9781424494408

Memristor has received significant attentions since Strukov et al released their invention on April 30, 2008 at Nature Letters. Based on the model of Strukov et al, analytic expression of the internal state is obtained by applying voltage to the device. By using the constant in the expression of the internal state, memory property of the memristor is explained. © 2011 IEEE.

关键词： Memristors

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A new method for ship classification and recognition

A new method for ship classification and recognition

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MIPPR 2005: image Analysis Techniques

作者： Zhao, Guangzhou Wang, Fei Zhang, Tianxu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China State Key Laboratory for Image Processing and Intelligent Control Wuhan 430074 China

This paper proposes a fast and robust algorithm for classification and recognition of ships based on the Principal Component Analysis (PCA) method. The three-dimensional ship models are achieved by modeling software of MultiGen, and then they are projected by Vega simulating software for two-dimensional ship silhouettes. The PCA method as against the Back-Propagation (BP) neural network method for simulated ship recognition using training and testing experiments, we can see that there is a sharp contrast between them. Some recognition results from simulated data are presented, the correct recognition rate of PCA method improved rapidly for each of the five ship types than that of neural network method, the number of times a ship type is recognized as one of the other ships is reduced greatly.

关键词： Classification (of information)

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Research on Linear Quadratic Robust control Algorithm for Non-stochastic Uncertain System 29

Research on Linear Quadratic Robust Control Algorithm for No...

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第29届中国控制与决策会议

作者： Jiaoru Huang Jiayue Ma Fucai Qian Chaobo Chen Xiaoru Song The International Joint Research Center of Autonomous Systems and Intelligent Control Xi'an Technological University Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology

ISBN: (纸本)9781509046584

A Linear Quadratic robust control algorithm is proposed for the system with non-stochastic *** this paper,the uncertainties are the noises which lie in a bounded ellipsoid *** assumption weakens the requirements of the known Gaussian distribution in the traditional Linear Quadratic Gaussian（LQG） *** on the linear characteristic of the system and robust optimization theory,the linear quadratic robust controller is *** simulation results show the effectiveness of the algorithm.

关键词： Non-stochastic uncertainties robust optimization Linear Quadratic robust control

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Salient object detection via color contrast and color distribution

Salient object detection via color contrast and color distri...

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11th Asian Conference on Computer Vision, ACCV 2012

作者： Fu, Keren Gong, Chen Yang, Jie Zhou, Yue Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai 200240 China

ISBN: (纸本)9783642373305

In this paper, we take the advantages of color contrast and color distribution to get high quality saliency maps. The overall procedure flow of our unified framework contains superpixel pre-segmentation, color contrast and color distribution computation, combination, final refinement and then object segmentation. During color contrast saliency computation, we combine two color systems and then introduce the using of distribution prior before saliency smoothing. It works to select correct color components. In addition, we propose a novel saliency smoothing procedure that is based on superpixel regions and is realized in color space. This processing step leads to total object being highlighted evenly, contributing to high quality color contrast saliency maps. Finally, a new refinement approach is utilized to eliminate artifacts and recover unconnected parts in the combined saliency maps. In visual comparison, our method produces higher quality saliency maps which stress out the total object meanwhile suppress background clutters. Both qualitative and quantitative experiments show our approach outperforms 8 state-of-the-art methods, achieving the highest precision rate 96% (3% improvement from the current highest), when evaluated via one of the most popular data sets [1]. Excellent content-aware image resizing also can be achieved with our saliency maps. © 2013 Springer-Verlag.

关键词： Superpixels

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A new change detection method based on non-parametric density estimation and Markov random fields

A new change detection method based on non-parametric densit...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Wang, Guiting Fan, Yuanzhang Jiao, Licheng Institute of Intelligent Information Processing Xidian University Xi'an 710071 China Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education of China China

ISBN: (纸本)9780819478085

A new change detection approach based on non-parametric density estimation and Markov random fields is proposed in this paper. As the concrete form of gray statistical distribution of remote sensing images is often difficult to be known, the non-parameter density estimation method does not need the specific forms in advance, and is especially suitable for the estimation problem of small samples, so we adopt the non-parametric density estimation method to obtain the precise estimation of the probability density of statistical distribution of differencing image in the paper, and then perform multitemporal remote sensing image change detection combining with MRF(Markov random fields)model for spatial smoothing. The final experimental results show that the proposed method is effective. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Probability distributions

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Computer simulation for medical ultrasound c-mode imaging based on 2d array

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2012 2nd International Conference on Materials Science and Information Technology, MSIT 2012

作者： Hua, Shaoyan Yuchi, Ming Ding, Mingyue Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Biomedical Engineering Department School of life Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9783037854389

C-mode imaging is one of the ultrasound imaging modalities. Compared with other modalities, e.g. A-mode, B-mode, M-mode, and Doppler, C-mode is mainly developed and used in industry testing. The potential of C-mode imaging for medical application has not been fully explored. In this paper, we design one 2-d plane array transducer through using the point spread function (PSF), and apply the 2d array transducer for C-mode imaging. The simulation results show that the generated C-mode images can display the anatomic structure and the pathological changes on the biological tissue. © (2012) Trans Tech Publications, Switzerland.

关键词： Optical transfer function

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Facial Expression Recognition In-the-Wild with Deep Pre-trained Models 17th

Facial Expression Recognition In-the-Wild with Deep Pre-tra...

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17th European Conference on Computer Vision, ECCV 2022

作者： Li, Siyang Xu, Yifan Wu, Huanyu Wu, Dongrui Yin, Yingjie Cao, Jiajiong Ding, Jingting Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Ant Group Hangzhou China

ISBN: (纸本)9783031250743

Facial expression recognition (FER) is challenging, when transiting from the laboratory to in-the-wild situations. In this paper, we present a general framework for the Learning from Synthetic Data Challenge in the 4th Affective Behavior Analysis In-The-Wild (ABAW4) competition, to learn as much knowledge as possible from synthetic faces with expressions. To cope with four problems in training robust deep FER models, including uncertain labels, class imbalance, mismatch between pretraining and downstream tasks, and incapability of a single model structure, our framework consists of four respective modules, which can be utilized for FER in-the-wild. Experimental results on the official validation set from the competition demonstrated that our proposed approach outperformed the baseline by a large margin. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Face recognition

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