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SAR image despeckling based on edge detection and nonsubsampled second generation bandelets

Journal of Systems Engineering and Electronics 2009年第3期20卷 519-526页

作者： Zhang Wenge~(1,2),Liu Fang~(1,2),Jiao Licheng~(2,3)& Gao Xinbo~(2,3) 1.School of Computer Science and technology,Xidian Univ.,Xi’an 710071,P.R.China 2.Key Lab.of intelligent perception and Image Understanding of Ministry of Education of China,Xi’an 710071,P.R.China 3.Inst,of intelligent information processing,Xidian Univ.,Xi’an 710071,P.R.China School of Computer Science and Technology Xidian Univ. Xi'an 710071 P. R. China Key Lab. of Intelligent Perception and Image Understanding of Ministry of Education of China Xi'an 710071 P. R. China Key Lab. of Intelligent Perception and Image Understanding of Ministry of Education of China Xi'an 710071 P. R. China Inst. of Intelligent Information Processing Xidian Univ. Xi'an 710071 P. R. China

To preserve the sharp features and details of the synthetic aperture radar （SAR） image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform （NSBT） domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges axe detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least square-Gaussian scale mixture （BLS-GSM）.

关键词： computer image processing synthetic aperture radar speckle edge detection nonsubsampled second generation bandelet transform Canny operator threshold shrinkage.

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Semantic Maximum Relevance and Modal Alignment for Cross-Modal Retrieval 11

Semantic Maximum Relevance and Modal Alignment for Cross-Mod...

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11th International Conference on Computing and Pattern Recognition, ICCPR 2022

作者： Sun, Pingping Qiang, Baohua Liu, Zhiguang Yang, Xianyi Xi, Guangyong Liu, Weigang Chen, Ruidong Zhang, Shihao Guilin University of Electronic Technology China The 54th Research Institute of Cetc Hebei Key Laboratory of Intelligent Information Perception and Processing China

ISBN: (纸本)9781450397056

With the increasing abundance of multimedia data resources, researches on mining the relationship between different modalities to achieve refined cross-modal retrieval are gradually emerging. In this paper, we propose a novel Semantic Maximum Relevance and Modal Alignment (SMR-MA) for Cross-Modal Retrieval, which utilizes the pre-trained model with abundant image text information to extract the features of each image text, and further promotes the modal information interaction between the same semantic categories through the modal alignment module and the multi-layer perceptron with shared weights. In addition, multi-modal embedding is distributed to the normalized hypersphere, and angular edge penalty is applied between feature embedding and weight in angular space to maximize the classification boundary, thus increasing both intra-class similarity and inter-class difference. Comprehensive analysis experiments on three benchmark datasets demonstrate that the proposed method has superior performance in cross-modal retrieval tasks and is significantly superior to the state-of-the-art cross-modal retrieval methods. © 2022 ACM.

关键词： Alignment

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Retraction Notice to "Reverse iontophoresis generated by porous microneedles produces an electroosmotic flow for glucose determination" [Talanta 267 (2024) 125156]

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Talanta 2025年 283卷 127102页

作者： Qi-Yao He Jia-Hao Zhao Shi-Ming Du De-Gui Li Zhi-Wei Luo Xue-Qiu You Jing Liu School of Navigation Jimei University Xiamen 361021 China Fujian Provincial Key Laboratory of Oceanic Information Perception and Intelligent Processing China. School of Marine Information Engineering Jimei University Xiamen 361021 China. School of Mechanical and Automotive Engineering Xiamen University of Technology Xiamen 361024 China. School of Marine Information Engineering Jimei University Xiamen 361021 China

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://***/about/policies/article-withdrawal). This article has been retracted at the request of the Editor-in-Chief. The authors have plagiarized part of a paper that had already appeared in Nat. Commun.12, (2021) 658, https://***/10.1038/s41467-021-20948-4. One of the conditions of submission of a paper for publication is that authors declare explicitly that their work is original and has not appeared in a publication elsewhere. Re-use of any data should be appropriately cited. As such this article represents a severe abuse of the scientific publishing system. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process.

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A miniaturized polarization-insensitive energy absorption metasurface 6

A miniaturized polarization-insensitive energy absorption me...

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2024 6th International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2024

作者： Zhen, Fajian Liu, Yunqing School of Electronic Information Engineering Changchun University of Science and Technology Jilin Changchun130022 China Jilin Provincial Science Technology Innovation Center of Intelligent Perception and Information Processing Jilin Changchun130022 China

A novel metasurface structure for energy absorption is proposed. The metasurface structure unit is composed of four bidirectional arrow patches, which are connected by load. In order to achieve unit miniaturization, a humanoid slot structure is proposed, which reduces the unit size to 0.23 λ. The designed metasurface structure can capture more than 90% of the energy at 5.8 GHz, has the characteristics of polarization insensitive, and can maintain 80% of the energy capture efficiency between 0 and 45°. The simulation results show that the structure is nonlinear to the load and can be applied to the design of rectification metasurface structures. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Polarization

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Facial emotion recognition based on auxiliary classifiers and SENet module 4

Facial emotion recognition based on auxiliary classifiers an...

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4th International Conference on Digital Signal and Computer Communications, DSCC 2024

作者： Shang, Yujie Yan, Fei Liu, Yunqing Li, Qi School of Electronic Information Engineering Changchun University of Science and Technology Jilin Province Changchun China Jilin Provincial Science and Technology Innovation Center of Intelligent Perception and Information Processing Jilin Province Changchun China

ISBN: (纸本)9781510681538

When using convolutional neural networks (CNNs) for facial emotion recognition, downsampling in the convolutional layers often leads to the loss of many features. These lost features also play a role in emotion recognition and can affect the effectiveness of emotion recognition. Therefore, we propose a facial emotion recognition method based on auxiliary classifiers and SENet modules to effectively alleviate the problem of feature loss during the convolution process. By using SENet modules, the model enhances its focus on different channel features during the feature extraction process, enabling the model to pay better attention to important features. Subsequently, auxiliary classifiers are introduced into the model to effectively utilize features extracted from different layers for auxiliary classification. Finally, the auxiliary classification results are adaptively weighted and fused with the main classifier's classification results. Experimental results demonstrate that introducing auxiliary classifiers and SENet modules further improves the model's accuracy, reaching 68.87%. © 2024 SPIE.

关键词： Emotion Recognition

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Exploiting boundary-isolated multiple edge-spanning tree for node shielding-based network robustness enhancement

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Expert Systems with Applications 2025年 287卷

作者： Wei Wei Mingkun Jiang Qinghui Zhang Peng Li Tao Ma Weidong Li Key Laboratory of Grain Information Processing and Control (Henan University of Technology) Ministry of Education Zhengzhou 450001 China Henan Key Laboratory of Grain Storage Information Intelligent Perception and Decision Making Henan University of Technology Zhengzhou 450001 China Institute for Complexity Science Henan University of Technology Zhengzhou 450001 China Beijing Institute of Technology No. 5 Zhongguancun South Street Haidian District Beijing 100086 China Ultimate IOT (Henan) Technology Ltd Zhengzhou 450001 China

As a critical network protection strategy, shielding vulnerable nodes can help build robust networks, where robustness can be generally measured using network connectivity, or complex metrics adapted to specific scenarios. However, the general connectivity-oriented node shielding is NP-hard and few methods can be applied in large-scale networks. The existing limited one can only achieve a far from optimal solution, where the core problem is that it shields the vulnerable part of the graph to infinite connectivity. We analyzed the spanning tree strategy and found a special kind of structure that is a superset of node cut sets, and any combination of nodes in the structure cannot form node cut sets smaller than the threshold. By using the structure as a boundary and shielding separate components, the algorithm can further prevent a large percentage of nodes from shielding without affecting robustness, and thus significantly reduce the cost of shielding. Experimental results in small and large scale graphs reveals that it is more than 10 5 times efficient than the optimal method while only introducing about 2 % extra cost. The shield ratio in large graphs can be more than 99.9 % and the cost saving ratio can be more than 60 % compared to the existing one, where the ratio is much lower in other heuristics.

关键词： Trees (mathematics)

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Abstractive Text Summarization Model Based on BERT Vectorization and Bidirectional Decoding

Abstractive Text Summarization Model Based on BERT Vectoriza...

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2023 International Conference on Cyber Security, Artificial Intelligence, and Digital Economy, CSAIDE 2023

作者： Teng, Keliang Qiang, Baohua Wang, Yufeng Yang, Xianyi Wang, Yuemeng Wang, Chen Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin541004 China Hebei Key Laboratory of Intelligent Information Perception and Processing The 54th Research Institute of CETC Shijiazhuang050081 China

ISBN: (纸本)9781510666597

Facing the pressure of the extremely inflated network information and data overload surplus, it is extremely important to locate "valuable information" efficiently and accurately. Text summarization technology in the field of Natural Language processing (NLP) is an effective means to analyze and process network information. In this paper, we propose an abstractive text summarization model based on bidirectional encoder representations from transformers (BERT) vectorization and bidirectional decoding. The BERT is adopted to obtain a more global vector representation, which helps the subsequent encoder and decoder to fuse the full-text information to generate a summary with high generality. The decoding phase adopts a bidirectional decoding structure and combines the attention mechanism to maintain the bilateral decoding result to generate summaries. The bidirectional decoding structure can be fine-tuned according to the bidirectional results, which can overcome the tilt problem of the unidirectional structure, and the generated summaries are more consistent. The experimental results on the NLPCC2017 text summarization dataset show that the summaries generated by our model have the higher coherence at the word and sentence level, and the stronger generalization of the full text. © 2023 SPIE.

关键词： Decoding

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Application research of general aircraft fault prognostic and health management technology 5th

Application research of general aircraft fault prognostic an...

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5th Euro-China Conference on intelligent Data Analysis and Applications, ECC 2018

作者： Changsheng, Liu Changyun, Li Min, Liu Ying, Cheng Jie, Huang Changsha Aeronautical Vocational and Technical College ChangshaHunan410014 China Hunan Key Laboratory of Intelligent Information Perception and Processing Technology ZhuzhouHunan412007 China

ISBN: (纸本)9783030037659

General aircrafts are very complicated to analyze from the perspective of structure and system, which means the maintenance task is very heavy. The traditional "broken-then- repair" and "planned repair" methods have serious shortcomings in dealing with the ever-changing new situation. "Maintenance depending on the situation" and "predictive maintenance" will nip the fault in the bud and become the direction of future system maintenance strategy development. This research studies three key technologies: general aircraft intelligent monitoring technology, general aircraft health assessment and prediction method based on multi-source big data fusion, and general aircraft operation and maintenance process visualization evolution simulation technology. Built on these technologies, a General Aviation Health Supervision platform is developed. This supervision platform is of great significance to improve the safety and reliability of general aviation aircraft, reduce operation and maintenance costs, and promote the development of the local navigation industry. The research outcome is tested on the Ararat SA60L light sport aircraft manufactured by Hunan Shanhe technology Co., Ltd. The test confirms that the general aviation health supervision platform, successfully provides real-time, systematic and intelligent solution for the monitoring and health supervision of general aviation aircrafts. It is expected that the new platform will create a revenue of more than 50 million yuan in the first three years of commercialization, with an annual growth rate of over 20%. © Springer Nature Switzerland AG 2019.

关键词： Health

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Attribute Selection Method Based on Artificial Bee Colony Algorithm and Neighborhood Discrimination Matrix Optimization 16th

Attribute Selection Method Based on Artificial Bee Colony Al...

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16th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2021

作者： Ji, Yuxuan Ye, Jun Yang, Zhenyu Ao, Jiaxin Wang, Lei Nanchang Institute of Technology Jiangxi Nanchang330000 China Key Laboratory of Water Information Cooperative Perception and Intelligent Processing of Jiangxi Province Jiangxi Nanchang330000 China

ISBN: (纸本)9789811912559

At present, the existing attribute reduction algorithm combining artificial bee colony and neighborhood rough set basically uses the attribute dependence and the number of attribute subsets as parameters to construct the fitness function, while ignoring the role of heuristic information. As a result, the number of bee colony iterations increases, and the convergence speed is slow. Aiming at this kind of problem, an improved method is proposed. First, a discernibility matrix under the neighborhood rough set is defined;secondly, an attribute importance measurement method of the discernibility matrix under the neighborhood decision system is proposed;The attribute importance of the domain discrimination matrix constructs a new fitness function for the heuristic factor;finally, an attribute selection algorithm for artificial bee colony algorithm and neighborhood discrimination matrix importance optimization is designed. Compared with the original algorithm, the new method reduces the number of generations, accelerates the convergence speed, and retains the minimum attribute reduction collected during each iteration, and multiple minimum attribute reductions can be obtained. The experimental results on the UCI data set prove the feasibility and effectiveness of the algorithm. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Matrix algebra

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Object Detection Algorithm Based on Coordinate Attention and Context Feature Enhancement 11

Object Detection Algorithm Based on Coordinate Attention and...

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11th International Conference on Computing and Pattern Recognition, ICCPR 2022

作者： Liu, Lingzhi Qiang, Baohua Wang, Yuanchun Yang, Xianyi Tian, Jubo Zhang, Shihao Guilin University of Electronic Technology Guilin China The 54th Research Institute of Cetc Shijiazhuang China Hebei Key Laboratory of Intelligent Information Perception and Processing Shijiazhuang China

ISBN: (纸本)9781450397056

In recent years, object detection has been widely used in various fields such as face detection, remote sensing image detection and pedestrian detection. Due to the complex environment in the actual scene, we need to fully obtain the feature information in the image to improve the accuracy of object detection. This paper proposes an object detection algorithm based on coordinate attention and contextual feature enhancement. We design a multi-scale attention feature pyramid network, which first uses multi-branch atrous convolution to capture multi-scale context information, and then fuses the coordinate attention mechanism to embed location information into channel attention, and finally uses a bidirectional feature pyramid structure to effectively fuse high-level features and low-level features. We also adopt the GIoU loss function to further improve the accuracy of object detection. The experimental results show that the proposed method has certain advantages compared with other detection algorithms in the PASCAL VOC datasets. © 2022 ACM.

关键词： Object detection

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