يعرض 1 - 10 نتائج من 207 نتيجة بحث عن '"uav multispectral"', وقت الاستعلام: 1.05s تنقيح النتائج
  1. 1
    دورية أكاديمية
    Field-Scale Precision: Predicting Grain Yield of Diverse Wheat Breeding Lines Using High-Throughput UAV Multispectral Imaging

    المؤلفون: Ali, N., Mohammed, A., Bais, A., Berraies, S., Ruan, Y., Cuthbert, R.D., Sangha, J.S.

    المصدر: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of. 17:11419-11433 2024

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  2. 2
    دورية أكاديمية
    Soil Salinity Inversion Model Based on BPNN Optimization Algorithm for UAV Multispectral Remote Sensing

    المؤلفون: Zhao, W., Ma, H., Zhou, C., Li, Z.

    المصدر: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of. 16:6038-6047 2023

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  3. 3
    كتاب إلكتروني
    Water Quality Inversion of UAV Multispectral Data Using Machine Learning

    المؤلفون: Fu, L.Aff14, Lo, Y.Aff14, Lu, T. C.Aff14, Zhang, C.Aff14

    المساهمون: di Prisco, Marco, Series EditorAff1, Chen, Sheng-Hong, Series EditorAff2, Vayas, Ioannis, Series EditorAff3, Kumar Shukla, Sanjay, Series EditorAff4, Sharma, Anuj, Series EditorAff5, Kumar, Nagesh, Series EditorAff6, Wang, Chien Ming, Series EditorAff7, Cui, Zhen-Dong, Series EditorAff8, Papadikis, Konstantinos, editorAff9, Zhang, Cheng, editorAff10, Tang, Shu, editorAff11, Liu, Engui, editorAff12, Di Sarno, Luigi, editorAff13

    المصدر: Towards a Carbon Neutral Future : The Proceedings of The 3rd International Conference on Sustainable Buildings and Structures. 393:357-365

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  4. 4
    دورية أكاديمية
    Wheat Yellow Rust Severity Detection by Efficient DF-UNet and UAV Multispectral Imagery

    المؤلفون: Zhang, T., Yang, Z., Xu, Z., Li, J.

    المصدر: IEEE Sensors Journal IEEE Sensors J. Sensors Journal, IEEE. 22(9):9057-9068 May, 2022

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  5. 5
    دورية أكاديمية
    Field-Scale Precision: Predicting Grain Yield of Diverse Wheat Breeding Lines Using High-Throughput UAV Multispectral Imaging

    المؤلفون: Nisar Ali, Ahmed Mohammed, Abdul Bais, Samia Berraies, Yuefeng Ruan, Richard D. Cuthbert, Jatinder S. Sangha

    المصدر: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11419-11433 (2024)

    مصطلحات موضوعية: Breeding varieties, field scale, machine learning (ML), plot detection model (YOLOv8), remote sensing, UAV multispectral imaging, Ocean engineering, TC1501-1800, Geophysics. Cosmic physics, QC801-809

    وصف الملف: electronic resource

    Relation: https://ieeexplore.ieee.org/document/10552912/; https://doaj.org/toc/1939-1404; https://doaj.org/toc/2151-1535

    URL الوصول: https://doaj.org/article/a6934d62974c4d01bbc9cf68694a0cae

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  6. 6
    دورية أكاديمية
    Machine learning algorithm inversion experiment and pollution analysis of water quality parameters in urban small and medium-sized rivers based on UAV multispectral data

    المؤلفون: Hou, YikaiAff1, Aff2, Zhang, AnbingAff3, IDs11356023279636_cor2, Lv, Rulan, Zhang, Yanping, Ma, Jie, Li, Ting

    المصدر: Environmental Science and Pollution Research. 30(32):78913-78932

    Find this article in full text from Springer Verlag. Find this article in full text from ProQuest Full Text Finder
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  7. 7
    دورية أكاديمية
    Improving the Spatial and Temporal Estimation of Maize Daytime Net Ecosystem Carbon Exchange Variation Based on Unmanned Aerial Vehicle Multispectral Remote Sensing

    المؤلفون: Peng, M., Han, W., Li, C., Huang, S.

    المصدر: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of. 14:10560-10570 2021

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  8. 8
    دورية أكاديمية
    Estimation of aboveground biomass from spectral and textural characteristics of paddy crop using UAV-multispectral images and machine learning techniques

    المؤلفون: Sudarsan Biswal, Navneet Pathak, Chandranath Chatterjee, Damodhara Rao Mailapalli

    المصدر: Geocarto International, Vol 39, Iss 1 (2024)

    مصطلحات موضوعية: Aboveground biomass, UAV-multispectral images, vegetation-indices, normalised difference texture indices (NDTIs), paddy crop, Physical geography, GB3-5030

    وصف الملف: electronic resource

    Relation: https://doaj.org/toc/1010-6049; https://doaj.org/toc/1752-0762

    URL الوصول: https://doaj.org/article/d1ecc4fdaf6041c98c3a8331af0fc03f

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  9. 9
    دورية أكاديمية
    Retrieval of chlorophyll content for vegetation communities under different inundation frequencies using UAV images and field measurements

    المؤلفون: Zhinan Lao, Bolin Fu, Yingying Wei, Tengfang Deng, Wen He, Yanli Yang, Hongchang He, Ertao Gao

    المصدر: Ecological Indicators, Vol 158, Iss , Pp 111329- (2024)

    مصطلحات موضوعية: Karst wetland, Vegetation communities, Inundation frequencies and water qualities, Chlorophyll content estimation, Remote sensing inversion, UAV multispectral images, Ecology, QH540-549.5

    وصف الملف: electronic resource

    Relation: http://www.sciencedirect.com/science/article/pii/S1470160X23014711; https://doaj.org/toc/1470-160X

    URL الوصول: https://doaj.org/article/2b32ef52a3494255933f7afc1918d019

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  10. 10
    دورية أكاديمية
    Prediction of vertical distribution of SPAD values within maize canopy based on unmanned aerial vehicles multispectral imagery

    المؤلفون: Bo Chen, Guanmin Huang, Xianju Lu, Shenghao Gu, Weiliang Wen, Guangtao Wang, Wushuai Chang, Xinyu Guo, Chunjiang Zhao

    المصدر: Frontiers in Plant Science, Vol 14 (2023)

    مصطلحات موضوعية: canopy chlorophyll, SPAD values, maize, UAV multispectral, vertical distribution, Plant culture, SB1-1110

    وصف الملف: electronic resource

    Relation: https://www.frontiersin.org/articles/10.3389/fpls.2023.1253536/full; https://doaj.org/toc/1664-462X

    URL الوصول: https://doaj.org/article/5aff4fc95c8e4d549fca32af3449f86b

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