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排序方式: 共有109条查询结果,搜索用时 15 毫秒
1.
Hai-Zhu Pan 《中国物理 B》2022,31(12):120701-120701
Benefiting from the development of hyperspectral imaging technology, hyperspectral image (HSI) classification has become a valuable direction in remote sensing image processing. Recently, researchers have found a connection between convolutional neural networks (CNNs) and Gabor filters. Therefore, some Gabor-based CNN methods have been proposed for HSI classification. However, most Gabor-based CNN methods still manually generate Gabor filters whose parameters are empirically set and remain unchanged during the CNN learning process. Moreover, these methods require patch cubes as network inputs. Such patch cubes may contain interference pixels, which will negatively affect the classification results. To address these problems, in this paper, we propose a learnable three-dimensional (3D) Gabor convolutional network with global affinity attention for HSI classification. More precisely, the learnable 3D Gabor convolution kernel is constructed by the 3D Gabor filter, which can be learned and updated during the training process. Furthermore, spatial and spectral global affinity attention modules are introduced to capture more discriminative features between spatial locations and spectral bands in the patch cube, thus alleviating the interfering pixels problem. Experimental results on three well-known HSI datasets (including two natural crop scenarios and one urban scenario) have demonstrated that the proposed network can achieve powerful classification performance and outperforms widely used machine-learning-based and deep-learning-based methods.  相似文献   
2.
PM2.5小时浓度多为单步预测。为实现PM2.5小时浓度的多步预测,基于“编码器-解码器”的序列-序列预测(Seq2Seq)模型,集合图卷积神经网络提取非欧式空间数据特征的能力以及注意力机制自适应关注特征的能力,提出了融合图卷积神经网络和注意力机制的PM2.5小时浓度多步预测(GCN_Attention_Seq2Seq)模型。并与Seq2Seq模型和使用了图卷积神经网络、未使用注意力机制的GCN_Seq2Seq模型进行了对照,以2015—2016年北京市22个空气质量监测站点的空气质量数据为样本进行实例验证,结果表明,Seq2Seq模型和图卷积神经网络(GCN)可对PM2.5小时浓度数据的时空依赖进行有效建模,注意力机制有助于减缓多步预测中的预测精度衰减,提升PM2.5小时浓度多步预测的精度。GCN_Attention_Seq2Seq模型可有效应用于多种长度的PM2.5浓度预测窗口。  相似文献   
3.
生物特征识别在信息安全领域发挥着重要作用,掌纹识别作为一种新型生物特征识别方式,具有低失真、非侵入性和高唯一性等优势。传统掌纹研究大多使用自然光成像系统以灰度格式获取,识别精度很难进一步提升。为了获得更多的身份鉴别信息,提出利用多光谱掌纹图像代替自然光掌纹图像。针对现有掌纹识别算法由于没有考虑到不同光谱的特性而导致纹理细节丢失,识别精准率低的问题,提出了一种基于多光谱图像融合的掌纹识别算法。该方法通过对不同光谱下的掌纹图像进行快速自适应二维经验模式分解(FABEMD),将多光谱掌纹图像分解成一系列频率由高到低的二维固有模态函数(BIMF)和一个残余分量,残余分量可被视为该光谱图像低频信息的初步估计。图像采集过程中光照条件很难保持稳定,而近红外光谱图像在进行FABEMD分解时对光照变换敏感,容易导致分解后的BIMF背景信息过于冗余;因此对分解后的近红外掌纹图像进行背景重建及特征细化,在对背景冗余信息进行平滑处理的同时可以有效增强高频信息的特征表达。为避免直接融合处理后引发的图像过度曝光问题,提出对近红外特征压缩后再融合。此外,提出了一种结合了注意力机制的改进残差网络(IRCANet),用于融合后的掌纹图像分类,在网络中引入分阶段残差结构,缓解了网络的退化问题,在学习过程中有效地减少信息丢失,对于融合后的多光谱掌纹图像,分阶段残差结构能够稳定地将图像信息在网络间传输,但对图像中的高低频信息区分效果不够显著,为了使网络关注更多区分性特征,利用特征通道间的相互依赖性,在分阶段残差结构中结合了通道注意力(Channel Attention)机制。最终,在香港理工大学(PolyU)多光谱掌纹数据集上进行的综合实验表明,该方法可以取得良好的效果,算法识别准确率能达到99.67%且具有良好的实时性。  相似文献   
4.
In this paper, we introduce a novel salient region detection algorithm by using background priors. Because of the fact that superpixel is perceptually more meaningful than pixel, and which can reduce the complexity of image processing, we use the superpixel algorithm to reprocess original images. In addition, we hold the point that the colors in the image boundary could mainly represent all background colors, hence we compute the color contrast between the intern colors and the boundary colors. Since the nearer the patches are close to center, the more they affect other patches, we propose a new distribution-based model. Finally, experimental results demonstrate that the proposed method outperforms the state-of-the-art approaches.  相似文献   
5.
Attention deficit hyperactivity disorder (ADHD) is characterized by decreased attention span, impulsiveness, and hyperactivity. Autonomic nervous system imbalance was previously described in this population. We aim to compare the autonomic function of children with ADHD and controls by analyzing heart rate variability (HRV). Children with ADHD (22 boys, mean age 9.964 years) and 28 controls (15 boys, mean age 9.857 years) rested in supine position with spontaneous breathing for 20 min. Heart rate was recorded beat by beat. HRV analysis was performed by use of chaotic global techniques. ADHD promoted an increase in the chaotic forward parameter. The algorithm which applied all three chaotic global parameters was only the second optimum statistically measured by Kruskal–Wallis (P < 0.0001) and low standard deviations. It was also highly influential by principal component analysis with almost all variation covered by the first two components. The third algorithm which lacked the (high spectral Detrended Fluctuation Analysis) parameter performed best statistically. However, we chose the algorithm which applied all three chaotic globals due to previous studies mentioned in the text—forward and inverse problems. Comparison of the autonomic function by analyzing HRV with chaotic global techniques suggests an increase in chaotic activity in children with ADHD in relation to the control group. © 2015 Wiley Periodicals, Inc. Complexity 21: 412–419, 2016  相似文献   
6.
This study investigates the behavioral indices of attention. A simple repetitive attentive task that resulted in mental fatigue was used consecutively in four trials. In the first step, reaction time and error responses were recorded to evaluate differences among trials. During the task, subjects showed different responses to stimulations. In the second part, to recognize the strategies, multiple clustering methods such as k‐means and fuzzy c‐means were performed in which behavioral indices and nonlinear features were used. In the last section, mental behavior was identified as a result of the chaotic properties of variations in reaction time. Therefore, the Lyapunov exponent of reaction times was evaluated. Results revealed that behavioral indices could distinguish attention from the occurrence of mental fatigue in trials. In addition, the three strategies used by subjects during the test protocol were assessed. Finally, variation of indices extracted from nonlinear analysis, that is, decrease in degree of chaotic behavior determined the transition from attention to mental fatigue. © 2012 Wiley Periodicals, Inc. Complexity, 2012  相似文献   
7.
罗辰辉  张伟  沈琼霞  叶波 《应用声学》2017,25(10):259-262
针对传统显著性模型在自然图像的显著性物体检测中存在的缺陷,提出了一种利用背景原型(background prototypes)进行对比的视觉关注模型,以实现显著性物体的检测与提取;传统显著性模型主要通过计算区域中心与四周区域差异性实现显著性检测,而自然场景中显著性区域和背景区域往往都存在较大差异,导致在复杂图像中难以获得理想检测效果;基于背景原型对比度的显著性物体检测方法在图像分割生成的超像素图基础上,选择距离图像中心较远的图像区域作为背景原型区域,通过计算图像中任意区域与这些背景原型区域的颜色对比度准确检测和提取图像中的显著性物体;实验结果表明,基于背景原型对比度的显著性模型可以更好地滤除杂乱背景,产生更稳定、准确的显著图,在准确率、召回率和F-measure等关键性能和直观视觉效果上均优于目前最先进的显著性模型,计算复杂度低,利于应用推广。  相似文献   
8.
视觉注意机制在图像增强中的应用研究   总被引:2,自引:0,他引:2  
将视觉注意机制引入到直方图构造中,并在此基础上提出了一种新的基于灰度级信息量直方图的图像增强算法.该算法利用Itti视觉注意计算模型对图像的显著性进行分析,获得全局显著图;然后,将全局显著图划分为若干等大的子区域,求取各子区域的平均显著值,并做归一化处理,得到子区域的加权统计系数;再将各子区域的灰度级加权统计值相加,得到灰度级信息量直方图;最后,依据直方图均衡化的映射函数,调整灰度级的动态范围.实验结果表明,该算法明显优于经典的GHE算法和AHE算法,具有满意的视觉效果.  相似文献   
9.
The aim of this paper is to expand the methodological spectrum of socially responsible investing by introducing stochastic sustainability returns into safety first models for portfolio choice. We provide a foundation of the notion of sustainability in portfolio theory and establish a general model for generalized safety first portfolio management with probabilistic constraints and three specifications of it. Moreover, we prove theorems about conditions for unique optimal solutions and for the constraints of one model being more restrictive than those of another. In an empirical part, we calculate the costs of investing according to our approach in terms of less financial return.  相似文献   
10.
司林  莫茜 《大学数学》2012,28(2):97-102
考虑到传染病的传播与股民数量的增长之间的类似性,建立了刻画新增股民数量变化规律的数学模型,并进行了相应的数学实验.建立的模型较好地反映了短期内新增股民数量的变化规律.  相似文献   
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