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Multi-Index Image Retrieval Hash Algorithm Based on Multi-View Feature Coding

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Computers, Materials & Continua 2020年第12期65卷 2335-2350页

作者： Rong Duan junshan tan jiaohua Qin Xuyu Xiang Yun tan n.eal nXiong College of Computer Science and Information Technology Central South University of Forestry&TechnologyChangsha410004China Department of Mathematics and Computer Science Northeastern State UniversityTahlequahOK 74464USA

In recent years,with the massive growth of image data,how to match the image required by users quickly and efficiently becomes a *** with single-view feature,multi-view feature is more accurate to describe image *** advantages of hash method in reducing data storage and improving efficiency also make us study how to effectively apply to large-scale image *** this paper,a hash algorithm of multi-index image retrieval based on multi-view feature coding is *** learning the data correlation between different views,this algorithm uses multi-view data with deeper level image semantics to achieve better retrieval *** algorithm uses a quantitative hash method to generate binary sequences,and uses the hash code generated by the association features to construct database inverted index files,so as to reduce the memory burden and promote the efficient *** order to reduce the matching error of hash code and ensure the retrieval accuracy,this algorithm uses inverted multi-index structure instead of single-index *** with other advanced image retrieval method,this method has better retrieval performance.

关键词： Hashing multi-view feature large-scale image retrieval feature coding feature matching

Maximal number of distinct H-eigenpairs for a two-dimensional real tensor

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Frontiers of Mathematics in China 2013年第1期8卷 85-105页

作者： Kelly j. PEARSOn tan ZHAnG Department of Mathematics and Statistics Murray State University Murray KY 42071-0009USA

Based on the generalized characteristic polynomial introduced by j. Canny in Generalized characteristic polynomials [j. Symbolic Comput., 1990, 9（3）： 241-250], it is immediate that for any m-order n-dimensional real tensor, the number of distinct H-eigenvalues is less than or equal to n（m-1）n-1. However, there is no known bounds on the maximal number of distinct H- eigenvectors in general. We prove that for any m ~〉 2, an m-order 2-dimensional tensor sd exists such that d has 2（m - 1） distinct H-eigenpairs. We give examples of 4-order 2-dimensional tensors with six distinct H-eigenvalues as well as six distinct H-eigenvectors. We demonstrate the structure of eigenpairs for a higher order tensor is far more complicated than that of a matrix. Further- more, we introduce a new class of weakly symmetric tensors, called p-symmetric tensors, and show under certain conditions, p-symmetry will effectively reduce the maximal number of distinct H-eigenveetors for a given two-dimensional tensor. Lastly, we provide a complete classification of the H-eigenvectors of a given 4-order 2-dimensional nonnegative p-symmetric tensor. Additionally, we give sufficient conditions which prevent a given 4-order 2-dimensional nonnegative irreducible weakly symmetric tensor from possessing six pairwise distinct H-eigenveetors.

关键词： Symmetric tensor H-eigenpairs

Adaptive Relaying Protocol for Decode and Forward Full-Duplex System over Rician Fading Channel: System Performance Analysis

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China Communications 2019年第3期16卷 92-102页

作者： tan n.nguyen Minh Tran Thanh-Long nguyen Miroslav Voznak Wireless Communications Research Group Faculty of Electrical and Electronics Engineering Ton Duc Thang University Optoelectronics Research Group Faculty of Electrical and Electronics Engineering Ton Duc Thang University Center for Information Technology Ho Chi Minh City University of Food Industry Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava

In this paper, the system performance of a decode-and-forward(DF) full-duplex(FD) adaptive relaying network over the Rician fading environment is proposed, analyzed and demonstrated. In the first stage, the system is presented with the energy harvesting and information transmission processes. After that, the analytical expressions of the achievable throughput, the outage probability, and symbol error ratio(SER) were proposed, analyzed and demonstrated. Finally, the analytical results are also demonstrated by Monte-Carlo simulation in comparison with the closed-form expressions in the influence of the key system parameters. The results show that the analytical and simulated results match for all possible parameter values.

关键词： relaying network throughput outage probability SER wireless energy harvesting(EH)

Performance Comparison of Mode-Locked Erbium-Doped Fiber Laser with nonlinear Polarization Rotation and Saturable Absorber Approaches

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Chinese Physics Letters 2012年第5期29卷 154-156页

作者： M.A.Ismail S.j.tan n.S.Shahabuddin S.W.Harun H.Arof H.Ahmad Department of Electrical Engineering Faculty of EngineeringUniversity of Malaya50603 Kuala LumpurMalaysia Photonics Research Center Department of PhysicsUniversity of Malaya50603 Kuala LumpurMalaysia

A mode-locked erbium-doped fiber laser (EDFL) is demonstrated using a highly concentrated erbium-doped fiber (EDF) as the gain medium in a ring configuration with and without a saturable absorber (SA).Without the SA,the proposed laser generates soliton pulses with a repetition rate of 12 MHz,pulse width of 1.11 ps and energy pulse of *** incorporating SA in the ring cavity,the optical output of the laser changes from soliton to stretched pulses due to the slight change in the group velocity *** the SA,a cleaner pulse is obtained with a repetition rate of 11.3 MHz,a pulse width of 0.58ps and a pulse energy of 2.3pj.

关键词： pulse fiber Erbium

AF-net:A Medical Image Segmentation network Based on Attention Mechanism and Feature Fusion

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Computers, Materials & Continua 2021年第11期69卷 1877-1891页

作者： Guimin Hou jiaohua Qin Xuyu Xiang Yun tan neal n.Xiong College of Computer Science and Information Technology Central South University of Forestry&TechnologyChangsha410004China Department of Mathematics and Computer Science Northeastern State UniversityTahlequah74464OKUSA

Medical image segmentation is an important application field of computer vision in medical image *** to the close location and high similarity of different organs in medical images,the current segmentation algorithms have problems with mis-segmentation and poor edge *** address these challenges,we propose a medical image segmentation network(AF-net)based on attention mechanism and feature fusion,which can effectively capture global information while focusing the network on the object *** this approach,we add dual attention blocks(DA-block)to the backbone network,which comprises parallel channels and spatial attention branches,to adaptively calibrate and weigh ***,the multi-scale feature fusion block(MFF-block)is proposed to obtain feature maps of different receptive domains and get multi-scale information with less computational ***,to restore the locations and shapes of organs,we adopt the global feature fusion blocks(GFF-block)to fuse high-level and low-level information,which can obtain accurate pixel *** evaluate our method on multiple datasets(the aorta and lungs dataset),and the experimental results achieve 94.0%in mIoU and 96.3%in DICE,showing that our approach performs better than U-net and other state-of-art methods.

关键词： Deep learning medical image segmentation feature fusion attention mechanism

Criss-Cross Attentional Siamese networks for Object Tracking

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Computers, Materials & Continua 2022年第11期73卷 2931-2946页

作者： Zhangdong Wang jiaohua Qin Xuyu Xiang Yun tan neal n.Xiong College of Computer Science and Information Technology Central South University of Forestry&TechnologyChangsha410004China Department of Mathematics and Computer Science Northeastern State UniversityTahlequah74464OKUSA

Visual object tracking is a hot topic in recent *** the meanwhile,Siamese networks have attracted extensive attention in this field because of its balanced precision and ***,most of the Siamese network methods can only distinguish foreground from the non-semantic *** fine-tuning and retraining of fully-convolutional Siamese networks for object tracking(SiamFC)can achieve higher precision under interferences,but the tracking accuracy is still not ideal,especially in the environment with more target interferences,dim light,and *** this paper,we propose crisscross attentional Siamese networks for object tracking(SiamCC).To solve the imbalance between foreground and non-semantic background,we use the feature enhancement module of criss-cross attention to greatly improve the accuracy of video object tracking in dim light and shadow *** results show that the maximum running speed of SiamCC in the object tracking benchmark dataset is 90 frames/*** terms of detection accuracy,the accuracy of shadow sequences is greatly improved,especially the accuracy score of sequence HUMAn8 is improved from 0.09 to 0.89 compared with the original SiamFC,and the success rate score is improved from 0.07 to 0.55.

关键词： Criss-cross attention object-tracking siamese-network

The cartography of plant immunity: Proximity labeling puts a novel SGT1–nSL1 regulatory module on the map

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Molecular Plant 2024年第11期17卷 1645-1647页

作者： Huang tan Chaonan Shi Alberto PMacho Rosa Lozano-Durán Department of Plant Biochemistry Center for Plant Molecular Biology(ZMBP)Eberhard Karls University72076 TübingenGermany Shanghai Center for Plant Stress Biology CAS Center for Excellence in Molecular Plant SciencesChinese Academy of SciencesShanghai 201602China These authors contributed equally to this article

Keeping immune responses in an off state in the absence of a threat is essential to avoid the deleterious consequences of autoimmunity,while their timely activation upon perception of non-self determines the capacity of an organism to defend against potential *** plants,constitutive or untimely activation of immune responses dramatically limits growth and reproduction,highlighting the essential role of negative regulators of immunity for plant *** a number of such regulators have been identified in the past couple of decades,the full complexity of the molecular mechanisms deployed by plants to ensure an appropriately controlled activation of immune responses,as well as their coordination with growth and development,are still largely elusive.

关键词： immunity consequences constitutive

Crystal Structure and Photochromism in Paint of 1,3,3-Trimethyl-6'-dihydro-indolinyl- spiro[2,3'-[3H]-naphtho[2,1-b][1,4]]oxazine

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Chinese journal of Structural Chemistry 2007年第5期26卷 572-574页

作者： tan Ting-Feng Department of Materials Science ＆ Engineering Tianjin Institute of Urban Construction Tianjin 300384 China

The title compound 2 （C30H27n3O, Mr = 445.55） has been synthesized and its structure was determined by X-ray crystallography method. The crystal is of monoclinic, space group P21/c with a = 17.520（15）, b = 8.640（7）, c = 15.439（13） A, β = 98.642（14）°, V = 2310（3） 3, Dc = 1.281 g/cm^3, μ = 0.780 mm^-1, F（000） = 944, Z = 4, the final R = 0.0671 and wR = 0.1790 for 1952 observed reflections with Ⅰ 〉 2σ（Ⅰ）. X-ray analysis revealed that the interatomic distance of C（20）O（1） is 1.464（4） , longer than that of the normal C-O bond （1.41～1.43 A） in the six-membered heterocycle, but this kind of change coincides with other spiro compounds. The six-membered heterocycle containing spiro Csp3-O is nonplanar. The UV-vis spectra of the title compound in polymer films showed that it exhibits excellent photochromic property.

关键词： spirooxazine crystal structure photochromism

Image Recognition of Citrus Diseases Based on Deep Learning

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Computers, Materials & Continua 2021年第1期66卷 457-466页

作者： Zongshuai Liu Xuyu Xiang jiaohua Qin Yun tan Qin Zhang neal n.Xiong Central South University of Forestry and Technology Changsha410004China School of Information Technology and Management Hunan University of Finance and EconomicsChangsha410205China Department of Mathematics and Computer Science Northeastern State UniversityTahlequahOK74464USA

In recent years,with the development of machine learning and deep learning,it is possible to identify and even control crop diseases by using electronic devices instead of manual *** this paper,an image recognition method of citrus diseases based on deep learning is *** built a citrus image dataset including six common citrus *** deep learning network is used to train and learn these images,which can effectively identify and classify crop *** the experiment,we use MobilenetV2 model as the primary network and compare it with other network models in the aspect of speed,model size,*** show that our method reduces the prediction time consumption and model size while keeping a good classification ***,we discuss the significance of using MobilenetV2 to identify and classify agricultural diseases in mobile terminal,and put forward relevant suggestions.

关键词： Deep learning image classification citrus diseases agriculture science and technology