These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

148 related articles for article (PubMed ID: 31379905)

  • 21. High-Throughput Switchgrass Phenotyping and Biomass Modeling by UAV.
    Li F; Piasecki C; Millwood RJ; Wolfe B; Mazarei M; Stewart CN
    Front Plant Sci; 2020; 11():574073. PubMed ID: 33193511
    [TBL] [Abstract][Full Text] [Related]  

  • 22. UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought.
    Ludovisi R; Tauro F; Salvati R; Khoury S; Mugnozza Scarascia G; Harfouche A
    Front Plant Sci; 2017; 8():1681. PubMed ID: 29021803
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Genetic dissection of seasonal vegetation index dynamics in maize through aerial based high-throughput phenotyping.
    Wang J; Li X; Guo T; Dzievit MJ; Yu X; Liu P; Price KP; Yu J
    Plant Genome; 2021 Nov; 14(3):e20155. PubMed ID: 34596348
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Estimation of Off-Target Dicamba Damage on Soybean Using UAV Imagery and Deep Learning.
    Tian F; Vieira CC; Zhou J; Zhou J; Chen P
    Sensors (Basel); 2023 Mar; 23(6):. PubMed ID: 36991952
    [TBL] [Abstract][Full Text] [Related]  

  • 25. High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates.
    Madec S; Baret F; de Solan B; Thomas S; Dutartre D; Jezequel S; Hemmerlé M; Colombeau G; Comar A
    Front Plant Sci; 2017; 8():2002. PubMed ID: 29230229
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Convolutional Neural Networks to Estimate Dry Matter Yield in a Guineagrass Breeding Program Using UAV Remote Sensing.
    de Oliveira GS; Marcato Junior J; Polidoro C; Osco LP; Siqueira H; Rodrigues L; Jank L; Barrios S; Valle C; Simeão R; Carromeu C; Silveira E; André de Castro Jorge L; Gonçalves W; Santos M; Matsubara E
    Sensors (Basel); 2021 Jun; 21(12):. PubMed ID: 34207543
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data.
    Han L; Yang G; Dai H; Xu B; Yang H; Feng H; Li Z; Yang X
    Plant Methods; 2019; 15():10. PubMed ID: 30740136
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Ramie Yield Estimation Based on UAV RGB Images.
    Fu H; Wang C; Cui G; She W; Zhao L
    Sensors (Basel); 2021 Jan; 21(2):. PubMed ID: 33477949
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Accuracy assessment of plant height using an unmanned aerial vehicle for quantitative genomic analysis in bread wheat.
    Hassan MA; Yang M; Fu L; Rasheed A; Zheng B; Xia X; Xiao Y; He Z
    Plant Methods; 2019; 15():37. PubMed ID: 31011362
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Quantitative Analysis of Cotton Canopy Size in Field Conditions Using a Consumer-Grade RGB-D Camera.
    Jiang Y; Li C; Paterson AH; Sun S; Xu R; Robertson J
    Front Plant Sci; 2017; 8():2233. PubMed ID: 29441074
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Coupling of machine learning methods to improve estimation of ground coverage from unmanned aerial vehicle (UAV) imagery for high-throughput phenotyping of crops.
    Hu P; Chapman SC; Zheng B
    Funct Plant Biol; 2021 Jul; 48(8):766-779. PubMed ID: 33663681
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Above-Ground Biomass Estimation in Oats Using UAV Remote Sensing and Machine Learning.
    Sharma P; Leigh L; Chang J; Maimaitijiang M; Caffé M
    Sensors (Basel); 2022 Jan; 22(2):. PubMed ID: 35062559
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Remote estimation of leaf area index (LAI) with unmanned aerial vehicle (UAV) imaging for different rice cultivars throughout the entire growing season.
    Gong Y; Yang K; Lin Z; Fang S; Wu X; Zhu R; Peng Y
    Plant Methods; 2021 Aug; 17(1):88. PubMed ID: 34376195
    [TBL] [Abstract][Full Text] [Related]  

  • 34. An efficient RGB-UAV-based platform for field almond tree phenotyping: 3-D architecture and flowering traits.
    López-Granados F; Torres-Sánchez J; Jiménez-Brenes FM; Arquero O; Lovera M; de Castro AI
    Plant Methods; 2019; 15():160. PubMed ID: 31889984
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Multi-Source Data Fusion Improves Time-Series Phenotype Accuracy in Maize under a Field High-Throughput Phenotyping Platform.
    Li Y; Wen W; Fan J; Gou W; Gu S; Lu X; Yu Z; Wang X; Guo X
    Plant Phenomics; 2023; 5():0043. PubMed ID: 37223316
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Field-based high-throughput phenotyping of plant height in sorghum using different sensing technologies.
    Wang X; Singh D; Marla S; Morris G; Poland J
    Plant Methods; 2018; 14():53. PubMed ID: 29997682
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Non-destructive monitoring of maize LAI by fusing UAV spectral and textural features.
    Sun X; Yang Z; Su P; Wei K; Wang Z; Yang C; Wang C; Qin M; Xiao L; Yang W; Zhang M; Song X; Feng M
    Front Plant Sci; 2023; 14():1158837. PubMed ID: 37063231
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Assessment of Multi-Image Unmanned Aerial Vehicle Based High-Throughput Field Phenotyping of Canopy Temperature.
    Perich G; Hund A; Anderegg J; Roth L; Boer MP; Walter A; Liebisch F; Aasen H
    Front Plant Sci; 2020; 11():150. PubMed ID: 32158459
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Improved Accuracy of High-Throughput Phenotyping From Unmanned Aerial Systems by Extracting Traits Directly From Orthorectified Images.
    Wang X; Silva P; Bello NM; Singh D; Evers B; Mondal S; Espinosa FP; Singh RP; Poland J
    Front Plant Sci; 2020; 11():587093. PubMed ID: 33193537
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Unmanned Aerial Vehicle-Based Phenotyping Using Morphometric and Spectral Analysis Can Quantify Responses of Wild Tomato Plants to Salinity Stress.
    Johansen K; Morton MJL; Malbeteau YM; Aragon B; Al-Mashharawi SK; Ziliani MG; Angel Y; Fiene GM; Negrão SSC; Mousa MAA; Tester MA; McCabe MF
    Front Plant Sci; 2019; 10():370. PubMed ID: 30984222
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.