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Frequency‐to‐spectrum mapping GAN for semisupervised hyperspectral anomaly detection

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1258-1273页

作者： Degang Wang Lianru Gao Ying Qu Xu Sun wenzhi liao Key Laboratory of Computational Optical Imaging Technology Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina College of Resources and Environment University of Chinese Academy of SciencesBeijingChina Faculty of Geographical Science Beijing Normal UniversityBeijingChina Flanders Make LommelBelgium Ghent University GhentBelgium

Most unsupervised or semisupervised hyperspectral anomaly detection(HAD)methods train background reconstruction models in the original spectral ***,due to the noise and spatial resolution limitations,there may be a lack of discrimination between backgrounds and *** makes it easy for the autoencoder to capture the lowlevel features shared between the two,thereby increasing the difficulty of separating anomalies from the backgrounds,which runs counter to the purpose of *** this end,the authors map the original spectrums to the fractional Fourier domain(FrFD)and reformulate it as a mapping task in which restoration errors are employed to distinguish background and *** study proposes a novel frequency‐to‐spectrum mapping generative adversarial network for ***,the depth separable features of backgrounds and anomalies are enhanced in the *** to the semisupervised approach,FTSGAN needs to learn the embedded features of the backgrounds,thus mapping and restoring them from the FrFD to the original spectral *** strategy effectively prevents the model from focussing on the numerical equivalence of input and output,and restricts the ability of FTSGAN to restore *** comparison and analysis of the experiments verify that the proposed method is competitive.

关键词： deep learning generative adversarial network hyperspectral image neural network semisupervised learning

A new kernel method for hyperspectral image feature extraction

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Geo-Spatial Information Science 2017年第4期20卷 309-318页

作者： Bin Zhao Lianru Gao wenzhi liao Bing Zhang Key Laboratory of Digital Earth Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Ringgold Standard Institution Beijing China Department of Telecommunications and Information Processing Ghent University Ghent Belgium

Hyperspectral image provides abundant spectral information for remote discrimination of subtle differences in ground ***,the increasing spectral dimensions,as well as the information redundancy,make the analysis and interpretation of hyperspectral images a *** extraction is a very important step for hyperspectral image *** extraction methods aim at reducing the dimension of data,while preserving as much information as ***,nonlinear feature extraction methods (*** minimum noise fraction (KMNF) transformation) have been reported to benefit many applications of hyperspectral remote sensing,due to their good preservation of high-order structures of the original ***,conventional KMNF or its extensions have some limitations on noise fraction estimation during the feature extraction,and this leads to poor performances for *** paper proposes a novel nonlinear feature extraction method for hyperspectral *** of estimating noise fraction by the nearest neighborhood information (within a sliding window),the proposed method explores the use of image *** approach benefits both noise fraction estimation and information preservation,and enables a significant improvement for *** results on two real hyperspectral images demonstrate the efficiency of the proposed *** to conventional KMNF,the improvements of the method on two hyperspectral image classification are 8 and 11％.This nonlinear feature extraction method can be also applied to other disciplines where high-dimensional data analysis is required.

关键词： Hyperspectral image dimensionality reduction feature extraction image segmentation kernel method

Detection of leaf structures in close-range hyperspectral images using morphological fusion

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Geo-Spatial Information Science 2017年第4期20卷 325-332页

作者： Gladys Villegas wenzhi liao Ronald Criollo Wilfried Philips Daniel Ochoa Department of Telecommunications and Information Processing Ghent University-imec Ghent Belgium Facultad de Ingeniería en Eléctrica y Computación ESPOL Polytechnic University Escuela Superior Politécnica del Litoral Guayaquil Ecuador

Close-range hyperspectral images are a promising source of information in plant biology,in particular,for in vivo study of physiological *** this study,we investigate how data fusion can improve the detection of leaf elements by combining pixel reflectance and morphological *** detection of image regions associated to the leaf structures is the first step toward quantitative analysis on the physical effects that genetic manipulation,disease infections,and environmental conditions have in *** tested our fusion approach on Musa acuminata (banana) leaf images and compared its discriminant capability to similar techniques used in remote *** results demonstrate the efficiency of our fusion approach,with significant improvements over some conventional methods.

关键词： Hyperspectral fusion morphology plant biology

Spatiotemporal change patterns of urban lakes in China’s major cities between 1990 and 2015

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International Journal of Digital Earth 2018年第11期11卷 1085-1102页

作者： Cong Xie Xin Huang Leiguang Wang Xing Fang wenzhi liao State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing(LIESMARS)Wuhan UniversityWuhanPeople’s Republic of China School of Remote Sensing and Information Engineering Wuhan UniversityWuhanPeople’s Republic of China School of Forestry Southwest Forestry UniversityKunmingPeople’s Republic of China School of Geodesy and Geomatics Wuhan UniversityWuhanPeople’s Republic of China Department of Telecommunications and Information Processing Ghent UniversityGhentBelgium State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijingPeople’s Republic of China

China has experienced unprecedented urbanization in the past decades,resulting in dramatic changes in the physical,limnological,and hydrological characteristics of lakes in urban ***,the spatiotemporal dynamics in distribution and abundance of urban lakes in China remain poorly ***,we characterized the spatiotemporal change patterns of urban lakes in China’s major cities between 1990 and 2015 using remote-sensing data and landscape *** results showed that the urban lake landscape patterns have experienced drastic changes over the past 25 *** total surface area of the urban lakes has decreased by 17,620.02 ha,a decrease of 24.22%,with a significant increase in the landscape fragmentation and a reduction in shape *** defined three lake-shrinkage types and found that vanishment was the most common lake-shrinkage pattern,followed by edge-shrinkage and tunneling in terms of lake ***,we also found that urban sprawl was the dominant driver of the lake shrinkage,accounting for 67.89%of the total area loss,and the transition from lakes to cropland was also an important factor(19.86%).This study has potential for providing critical baseline information for government decision-making in lake resources management and urban landscape design.

关键词： Urban expansion lake changes landscape pattern human activities

Information extraction from remote sensing imagery

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Geo-Spatial Information Science 2017年第4期20卷 297-298页

作者： Xin Huang Jiayi Li wenzhi liao Jocelyn Chanussot School of Remote Sensing and Information Engineering Wuhan University China TELIN-IPI-IMEC Ghent University Belgium Grenoble Institute of Technology France

Various platforms,such as satellite,aircraft,ground-based,some emerging aspects (***) have resulted in a dramatic improvement in the capabilities of earth observations (EO).The numerous remote sensing data promote an enhanced possibility to assess,monitor,and predict the dynamics of land-covers,anthropologic processes,and influence to the ***,the properties of the data acquired by such diverse sources pose challenges to the processing methodologies,and hence,development of a series of new methods for the analysis of remote sensing images is required,The aim of this special issue of Geospatial Information Science is to develop new ideas and technologies to facilitate the utility of remote sensing data and to further explore its potential in various applications.

关键词： Information retrieval

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截水帷幕在某基坑工程中的应用

湖北理工学院学报 2023年第6期39卷 37-40页

作者：廖文智闽武长城建设发展有限公司福建福州350013

强透水卵石层中搅拌桩不易成型且施工难度大,基坑开挖过程中,强透水地层易发生流土管涌等事故,且会引起基坑周边地面沉降,引发安全事故。文章结合工程实例,阐述了某基坑工程初次使用搅拌桩截水帷幕发生的流土现象,基坑周边地面沉降严重... 详细信息

强透水卵石层中搅拌桩不易成型且施工难度大,基坑开挖过程中,强透水地层易发生流土管涌等事故,且会引起基坑周边地面沉降,引发安全事故。文章结合工程实例,阐述了某基坑工程初次使用搅拌桩截水帷幕发生的流土现象,基坑周边地面沉降严重;结合现场实际情况,经计算分析后采用咬合桩截水帷幕进行截水。结果表明,在深厚含水层中开挖浅基坑采用悬挂式截水帷幕时,应考虑各种不利因素,确保计算结果符合实际情况,避免由于设计缺陷而引发安全事故。

关键词：基坑地下水控制地面沉降截水帷幕基坑监测

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“两墙合一”双环形支撑体系基坑变形特性分析

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岩土工程技术 2023年第6期37卷 669-675页

作者：周尧苗向光廖文智江杰张鹏中铁建设集团南方工程有限公司广西南宁530000 广西大学土木建筑工程学院广西南宁530004

南宁市某基坑采用“两墙合一”双环形支撑体系,为研究基坑开挖工况下地下连续墙及坑外浅基础建筑物的变形特性,基于现场监测资料,对基坑开挖引起的临近建筑物沉降、地连墙顶水平位移、竖向位移以及地连墙墙体侧向位移进行了系统分析。... 详细信息

南宁市某基坑采用“两墙合一”双环形支撑体系,为研究基坑开挖工况下地下连续墙及坑外浅基础建筑物的变形特性,基于现场监测资料,对基坑开挖引起的临近建筑物沉降、地连墙顶水平位移、竖向位移以及地连墙墙体侧向位移进行了系统分析。分析结果表明:周边建筑物沉降受其高度、基础形式、埋深、距基坑距离以及与基坑相对位置等因素的影响程度较大;地连墙竖向变形受基坑开挖暴露时间以及临近建筑物的影响较大,其最大竖向位移VWY变化区间为(-0.088%~0.083%) He(He为开挖深度);近建筑物段地连墙侧移呈现为“内凸悬臂复合式”变形形态;“坑角效应”导致位于坑角处的地连墙呈现出“阶梯内凸式”变形形态;地连墙的最大侧移变化区间为(0.02%~0.21%)He,平均值为0.085%He。

关键词：基坑开挖两墙合一建筑物沉降双环形支撑

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表象训练在初中足球教学中的应用研究

当代家庭教育 2021年第20期 125-126页

作者：廖文治福建省福州市永泰县第一中学

足球自古以来就深受国人的喜爱,是家喻户晓的球类运动,党的十八大以来,体育作为国家改革的重要组成部分,得到了党中央、国务院的高度重视,在这一背景下,青少年作为足球事业发展的后备力量,成为我国足球事业的重中之重。而表象训练法作... 详细信息

足球自古以来就深受国人的喜爱,是家喻户晓的球类运动,党的十八大以来,体育作为国家改革的重要组成部分,得到了党中央、国务院的高度重视,在这一背景下,青少年作为足球事业发展的后备力量,成为我国足球事业的重中之重。而表象训练法作为常见的足球教学方式之一,可以提高学生的技能和水平,基于此,本文主要针对当前初中足球教学现状,探索表象训练法在足球教学中的有效应用。

关键词：表象训练法初中足球教学现状有效应用

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深度强化学习求解移动机器人端到端导航问题的研究综述

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计算机工程与应用 2024年第14期60卷 1-13页

作者：何丽姚佳程廖雨鑫张文智卢赵清袁亮肖文东新疆大学智能制造现代产业学院(机械工程学院) 乌鲁木齐830017 北京化工大学信息科学与技术学院北京100029

自主导航是移动机器人完成复杂任务的前提和基础,传统的自主导航系统依赖于地图的精度,无法适应高度复杂的作业和服务场景。移动机器人不依赖先验地图信息,通过深度强化学习与环境交互学习能够自主决策的端到端导航方法成为新的研究热... 详细信息

自主导航是移动机器人完成复杂任务的前提和基础,传统的自主导航系统依赖于地图的精度,无法适应高度复杂的作业和服务场景。移动机器人不依赖先验地图信息,通过深度强化学习与环境交互学习能够自主决策的端到端导航方法成为新的研究热点。大多数现有的分类方法不能全面地总结端到端导航问题的挑战和机遇,根据端到端导航系统的特点,将导航问题的挑战归结为导航智能体感知能力差、学习效率低和导航策略泛化能力弱等关键问题,阐述了端到端导航系统的研究现状和发展趋势,分别详细介绍了近年来针对这些关键问题的代表性研究成果,并对其优势和不足进行了归纳总结。最后,从视觉语言导航、多智能体协同导航、融合超分辨率重建图像的端到端导航和可解释性端到端导航等方面展望了移动机器人端到端导航的未来发展趋势,为移动机器人端到端导航的研究和应用提供一定的思路。

关键词：端到端导航深度强化学习感知能力学习效率泛化能力

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