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9篇 您的检索式:作者名="G.Alexander"
    题名 作者 年代 出处 被引量
1Standards for ecologically successful river restoration显示文摘M.A.PALMER E.S.BERNHARDT J. D.ALLAN P.S.LAKE G.ALEXANDER S.BROOKS J.CARR S.CLAYTON C. N.DAHM J.FOLLSTAD SHAH D. L.GALAT S. G.LOSS P.GOODWIN D.D.HART B.HASSETT R.JENKINSON G.M.KONDOLF R.LAVE J.L.MEYER T.K.O’DONNELL L.PAGANO E.SUDDUTH 2005Journal of Applied Ecology2005,,2:2
2机车动车用分散式控制系统MITRAC显示文摘MITRAC控制系统是机车动车电子设备的支柱,它由分散布置的输入/输出单元、高效能的计算机、必需的控制和诊断软件以及统一的通信设施组成。该通信设施以机车车辆多功能总线为基础。所有硬件模块各自装在本身带有电源的外壳内,不需要层插件机箱。文章以分散式控制技术、使用的硬件模块和软件结构的基本设计为重点介绍了MITRAC控制系统。G.Alexander 王渤洪 1998大功率变流技术1998,,4:2
3Image Theory, Social Identity, and Social Dominance: Structural Characteristics and Individual Motives Underlying International Images显示文摘Michele G.Alexander ShanaLevin P. J.Henry 2005Political Psychology2005,,1:1
4Corporate Social Responsibility and Stock Market Performance显示文摘G.Alexander R.Bucholtz 0,,21:1
5Standards for ecologically successful river restoration显示文摘M.A.PALMER E.S.BERNHARDT J. D.ALLAN P.S.LAKE G.ALEXANDER S.BROOKS J.CARR S.CLAYTON C. N.DAHM J.FOLLSTAD SHAH D. L.GALAT S. G.LOSS P.GOODWIN D.D.HART B.HASSETT R.JENKINSON G.M.KONDOLF R.LAVE J.L.MEYER T.K.O’DONNELL L.PAGANO E.SUDDUTH 2005Journal of Applied Ecology2005,,2:1
6Outcomes after resection of giant emphysematous bullae显示文摘Paul H. Schipper Bryan F. Meyers Richard J. Battafarano Tracey J. Guthrie G.Alexander Patterson Joel D. Cooper 2004The Annals of Thoracic Surgery2004,,3:1
7Molecular staging of lung cancer: Real-time polymerase chain reaction estimation of lymph node micrometastatic tumor cell burden in stage I non-small cell lung cancer—preliminary results of cancer and leukemia group B trial 9761显示文摘Jonathan D’Cunha Angela L. Corfits James E. Herndon Jeffrey A. Kern Leslie J. Kohman G.Alexander Patterson Robert A. Kratzke Michael A. Maddaus 2002The Journal of Thoracic and Cardiovascular Surgery2002,,3:1
8Nitrogen management in bioreactor landfills显示文摘G.Alexander Price Morton A. Barlaz Gary R. Hater 2003Waste Management2003,,7:1
9Fusion of thermal and RGB images for automated deep learning based crack detection in civil infrastructure显示文摘Research has been continually growing toward the development of image-based structural health monitoring tools that can leverage deep learning models to automate damage detection in civil infrastructure.However,these tools are typically based on RGB images,which work well under ideal lighting conditions,but often have degrading performance in poor and low-light scenes.On the other hand,thermal images,while lacking in crispness of details,do not show the same degradation of performance in changing lighting conditions.The potential to enhance automated damage detection by fusing RGB and thermal images together within a deep learning network has yet to be explored.In this paper,RGB and thermal images are fused in a ResNET-based semantic segmentation model for vision-based inspections.A convolutional neural network is then employed to automatically identify damage defects in concrete.The model uses a thermal and RGB encoder to combine the features detected from both spectrums to improve its performance of the model,and a single decoder to predict the classes.The results suggest that this RGB-thermal fusion network outperforms the RGB-only network in the detection of cracks using the Intersection Over Union(IOU)performance metric.The RGB-thermal fusion model not only detected damage at a higher performance rate,but it also performed much better in differentiating the types of damage.Quincy G.Alexander Vedhus Hoskere Yasutaka Narazaki Andrew Maxwell Billie F.Spencer Jr 2022AI in Civil Engineering2022,1,1:0
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