摘要：Facial expression recognition(FER)is still challenging due to the small interclass discrepancy in facial expression data.In view of the significance of facial crucial regions for FER,many existing
Facial expression recognitiondeep neural networkmultiple network ensembleattention networkfacial crucial regions
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2.Spatial improved fuzzy c-means clustering for image segmentation
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conference_WFHYXW485847
[会议论文]Feng ZhaoLicheng Jiao20112011 International Conference on Electronic & Mechanical Engineering and Information Technology(EMEIT 2011)(2011年机电工程与信息技术国际会议)
摘要：The generalized fuzzy c-means clustering algorithm with improved fuzzy partition (GFCM) is a new modified version of the fuzzy c-means clustering algorithm (FCM). GFCM under appropriate parameters
3.Moitf GibbsGA: Sampling transcription factor binding sites coupled with PSFM optimization by GA
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conference_WFHYXW385588
[会议论文]Lifang LiuLicheng Jiao2009The 4th International Symposium on Intelligence Computation and Applications(第四届智能计算及其应用国际会议 ISICA2009)
摘要：Identification of transcription factor binding sites (TFBSs) or motifs plays an important role in deciphering the mechanisms of gene regulation. Although many experimental and computational methods
引用
下载：1
4.Eye Detection under Varying Illumination using the Retinex Theory
摘要： Eye detection plays an important role in face recognition because eyes provide distinctive facial features.However, illumination effects such as heavy shadows and drastic lighting change make it
5.A Semi-Supervised Deep Fuzzy C-Mean Clustering for Two Classes Classification
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conference_WFHYXW633277
[会议论文]Ali ArshadSaman RiazLicheng JiaoAparna Murthy20172017 IEEE 3rd Information Technology and Mechatronics Engineering Conference(ITOEC2017)(2017 IEEE 第3届信息技术与机电一体化工程国际学术会议)
摘要： Deep Fuzzy C-Means algorithm is applied to determine veiled structure in the data set.It is commonly used when data boundaries are not clearly defined and extra parameters are needed to reduce the
6.Particle Swarm Optimization Based Clustering: A Comparison of Different Cluster Validity Indices
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conference_WFHYXW422746
[会议论文]Ruochen LiuXiaojuan SunLicheng Jiao2010International Conference on Life System Modeling and Simulation,and International Conference on Intelligent Computing for Sustainable Energy and Environment(2010生命系统建模与仿真国际会议暨m2010可持续能源与环境智能计算国际会议)
摘要：Most of clustering algorithms based on natural computation aim to find the proper partition of data to be processed by optimizing certain criteria, socalled as cluster validity index, which must be
7.Clonal Selection Classification Algorithm for High-Dimensional Data
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conference_WFHYXW422743
[会议论文]Ruochen LiuPing ZhangLicheng Jiao2010International Conference on Life System Modeling and Simulation,and International Conference on Intelligent Computing for Sustainable Energy and Environment(2010生命系统建模与仿真国际会议暨m2010可持续能源与环境智能计算国际会议)
摘要：Many important problems involve classifying highdimensional data sets, which is very difficult because learning methods suffer from the curse of dimensionality. In this paper, Clonal Selection
摘要：In this paper,we present a new method of change detection in SAR images based on multiscale product of wavelet transform and PCA algorithm. This method applied multiscale product of wavelet
Multiscale productPCAChange detection
引用
被引：1下载：2
9.SAR Image Segmentation Based on Gabor Filters of Adaptive window In Overcomplete Brushlet Domain
摘要：In this paper,a new technique based on Gabor filters with adaptive window is proposed for SAR image segmentation in overcomplete brushlet domain.SAR image is full of texture and direction
SAR image segmentationovercomplete brushletgray-level cooccurrence probability (GLCP)Gabor filtersAdaptive window
引用
被引：2下载：3
10.A change detection algorithm based on object feature for SAR image
摘要：In the detection of change objects of SAR images,regard to the images containing high intensity noise,traditional methods will produce a considerable false alarm. This paper presents a new method
Change detectiondirection measureregion blocksmulti-threshold and object
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下载：1
11.An Automatic Bridge Detection Technique for High Resolution SAR Images
摘要：In this paper,an approach for detecting bridges over water bodies from high resolution SAR images is presented.It consists of two steps:water extraction and bridge detection. A method based on
Classificationporosityline detection
引用
被引：2下载：6
12.SAR Image Segmentation using Quantum Clonal Selection Clustering
摘要：A novel clustering algorithm is proposed,which is derived from physical intuition of quantum mechanics and biological principle based on immune clonal selection. As extension ideas of scale-space
摘要：A new method about SAR image despeckling is proposed in this paper,this method is achieved by combining wavelet kernel transform (WKT) and Gaussian Scale Mixture model (GSM).WKT is a multiscale
摘要：The nonlocal (NL) means filter as a recent denoising approach has demonstrated its empirical merit for additive Gaussian noise.In this paper,a novel Bayesian nonlocal (BNL) means filter is derived
NL meansBayesiandespecklingSAR
引用
被引：1下载：8
15.A Contourlet-based Interpolation Restoration Method for Super-resolution of SAR Image
摘要：As is weH known that the quality of a digital image is affected by many factors,such as the distance between the acquisition system and the object,the acquisition environment conditions,and the
摘要：A new method for automated road extraction in remote sensing images is proposed based on Nonsubsampled contourlet Transform (NSCT).Due to the advantages of multi-scale,multi-direction and translation
摘要：A novel method of speckle suppression for SAR image based on the curvelet transform is presented. A Bayesian shrinkage factor is derived to shrink the curvelet coefficients,then the mean filter
18.Isomerous Multiple Classifier Ensemble Method with SVM and KMP
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conference_WFHYXW328805
[会议论文]Gou ShuipingMao ShashaLicheng Jiao20082008 International Conference on Audio，Language and Image Processing(2008国际声音、语言、图像过程大会)
摘要：A method for multi-classifier ensemble of Support Vector Machine ensemble (SVMs) and Kernel Matching Pursuit Ensemble (KMPs) is proposed. Support Vector Machine has advantage in solving
引用
下载：1
19.A Rough Set Describe Method for Real Function Continuous Theorem
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conference_WFHYXW171074
[会议论文]Yongquan ZhouYindong YangLicheng Jiao2006Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)
摘要：In this paper, a rough set describes method for real functions continuous theorem (the monotone convergence theorem, the Bollzano-Weierstrass theorem, and the nested interval theorem) is proposed.
Rough set theoryreal continuous functionslower approximationupper approximationJunction continuous theoreminterval series convergenceiterative method.
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20.Domain Adversarial Debiased Self-Training for Hyperspectral Image Classification
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conference_5224cd0d159b992d0c16a22554905db4
[会议论文]Tianshu ZhangJie FengZiyu ZhouXiangrong ZhangLicheng Jiao2023IEEE International Geoscience and Remote Sensing Symposium
摘要：Unsupervised domain adaptation (UDA) has been widely used in hyperspectral image (HSI) classification. Domain adversarial learning methods and self-training methods are two major UDA methods. Most
Geoscience and remote sensingAdversarial machine learningRobustnessTask analysisHyperspectral imagingImage classification
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