BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

115 related articles for article (PubMed ID: 38903425)

  • 1. Estimation of soybean yield based on high-throughput phenotyping and machine learning.
    Li X; Chen M; He S; Xu X; He L; Wang L; Gao Y; Tang F; Gong T; Wang W; Xu M; Liu C; Yu L; Liu W; Yang W
    Front Plant Sci; 2024; 15():1395760. PubMed ID: 38903425
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A Novel Approach to Pod Count Estimation Using a Depth Camera in Support of Soybean Breeding Applications.
    Mathew J; Delavarpour N; Miranda C; Stenger J; Zhang Z; Aduteye J; Flores P
    Sensors (Basel); 2023 Jul; 23(14):. PubMed ID: 37514799
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Soybean leaf estimation based on RGB images and machine learning methods.
    Li X; Xu X; Xiang S; Chen M; He S; Wang W; Xu M; Liu C; Yu L; Liu W; Yang W
    Plant Methods; 2023 Jun; 19(1):59. PubMed ID: 37330499
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. Image-based phenotyping of seed architectural traits and prediction of seed weight using machine learning models in soybean.
    Duc NT; Ramlal A; Rajendran A; Raju D; Lal SK; Kumar S; Sahoo RN; Chinnusamy V
    Front Plant Sci; 2023; 14():1206357. PubMed ID: 37771485
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Yield prediction by machine learning from UAS-based mulit-sensor data fusion in soybean.
    Herrero-Huerta M; Rodriguez-Gonzalvez P; Rainey KM
    Plant Methods; 2020; 16():78. PubMed ID: 32514286
    [TBL] [Abstract][Full Text] [Related]  

  • 7. High-throughput phenotyping for non-destructive estimation of soybean fresh biomass using a machine learning model and temporal UAV data.
    Ranđelović P; Đorđević V; Miladinović J; Prodanović S; Ćeran M; Vollmann J
    Plant Methods; 2023 Aug; 19(1):89. PubMed ID: 37633921
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Estimation of soybean yield parameters under lodging conditions using RGB information from unmanned aerial vehicles.
    Bai D; Li D; Zhao C; Wang Z; Shao M; Guo B; Liu Y; Wang Q; Li J; Guo S; Wang R; Li YH; Qiu LJ; Jin X
    Front Plant Sci; 2022; 13():1012293. PubMed ID: 36589058
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Utilizing Spectral, Structural and Textural Features for Estimating Oat Above-Ground Biomass Using UAV-Based Multispectral Data and Machine Learning.
    Dhakal R; Maimaitijiang M; Chang J; Caffe M
    Sensors (Basel); 2023 Dec; 23(24):. PubMed ID: 38139554
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Application of Machine Learning Algorithms in Plant Breeding: Predicting Yield From Hyperspectral Reflectance in Soybean.
    Yoosefzadeh-Najafabadi M; Earl HJ; Tulpan D; Sulik J; Eskandari M
    Front Plant Sci; 2020; 11():624273. PubMed ID: 33510761
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Monitoring of Nitrogen Concentration in Soybean Leaves at Multiple Spatial Vertical Scales Based on Spectral Parameters.
    Sun T; Li Z; Wang Z; Liu Y; Zhu Z; Zhao Y; Xie W; Cui S; Chen G; Yang W; Zhang Z; Zhang F
    Plants (Basel); 2024 Jan; 13(1):. PubMed ID: 38202447
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Application of UAV Multisensor Data and Ensemble Approach for High-Throughput Estimation of Maize Phenotyping Traits.
    Shu M; Fei S; Zhang B; Yang X; Guo Y; Li B; Ma Y
    Plant Phenomics; 2022; 2022():9802585. PubMed ID: 36158531
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Early Prediction of Soybean Traits through Color and Texture Features of Canopy RGB Imagery.
    Yuan W; Wijewardane NK; Jenkins S; Bai G; Ge Y; Graef GL
    Sci Rep; 2019 Oct; 9(1):14089. PubMed ID: 31575995
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Application of machine learning and genetic optimization algorithms for modeling and optimizing soybean yield using its component traits.
    Yoosefzadeh-Najafabadi M; Tulpan D; Eskandari M
    PLoS One; 2021; 16(4):e0250665. PubMed ID: 33930039
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Soybean (
    Yang W; Li Z; Chen G; Cui S; Wu Y; Liu X; Meng W; Liu Y; He J; Liu D; Zhou Y; Tang Z; Xiang Y; Zhang F
    Plants (Basel); 2024 May; 13(11):. PubMed ID: 38891307
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Improving the efficiency of soybean breeding with high-throughput canopy phenotyping.
    Moreira FF; Hearst AA; Cherkauer KA; Rainey KM
    Plant Methods; 2019; 15():139. PubMed ID: 31827576
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Cotton Yield Estimation Based on Vegetation Indices and Texture Features Derived From RGB Image.
    Ma Y; Ma L; Zhang Q; Huang C; Yi X; Chen X; Hou T; Lv X; Zhang Z
    Front Plant Sci; 2022; 13():925986. PubMed ID: 35783985
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Improve Soybean Variety Selection Accuracy Using UAV-Based High-Throughput Phenotyping Technology.
    Zhou J; Beche E; Vieira CC; Yungbluth D; Zhou J; Scaboo A; Chen P
    Front Plant Sci; 2021; 12():768742. PubMed ID: 35087547
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.