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 *

156 related articles for article (PubMed ID: 39148622)

  • 1. Cotton morphological traits tracking through spatiotemporal registration of terrestrial laser scanning time-series data.
    Rodriguez-Sanchez J; Snider JL; Johnsen K; Li C
    Front Plant Sci; 2024; 15():1436120. PubMed ID: 39148622
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Terrestrial 3D laser scanning to track the increase in canopy height of both monocot and dicot crop species under field conditions.
    Friedli M; Kirchgessner N; Grieder C; Liebisch F; Mannale M; Walter A
    Plant Methods; 2016; 12():9. PubMed ID: 26834822
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Automatic Registration of TLS-TLS and TLS-MLS Point Clouds Using a Genetic Algorithm.
    Yan L; Tan J; Liu H; Xie H; Chen C
    Sensors (Basel); 2017 Aug; 17(9):. PubMed ID: 28850100
    [TBL] [Abstract][Full Text] [Related]  

  • 4. In-field High Throughput Phenotyping and Cotton Plant Growth Analysis Using LiDAR.
    Sun S; Li C; Paterson AH; Jiang Y; Xu R; Robertson JS; Snider JL; Chee PW
    Front Plant Sci; 2018; 9():16. PubMed ID: 29403522
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Development of a Low-Cost System for 3D Orchard Mapping Integrating UGV and LiDAR.
    Murcia HF; Tilaguy S; Ouazaa S
    Plants (Basel); 2021 Dec; 10(12):. PubMed ID: 34961275
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Registration of spatio-temporal point clouds of plants for phenotyping.
    Chebrolu N; Magistri F; Läbe T; Stachniss C
    PLoS One; 2021; 16(2):e0247243. PubMed ID: 33630896
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Crop 3D-a LiDAR based platform for 3D high-throughput crop phenotyping.
    Guo Q; Wu F; Pang S; Zhao X; Chen L; Liu J; Xue B; Xu G; Li L; Jing H; Chu C
    Sci China Life Sci; 2018 Mar; 61(3):328-339. PubMed ID: 28616808
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Direct derivation of maize plant and crop height from low-cost time-of-flight camera measurements.
    Hämmerle M; Höfle B
    Plant Methods; 2016; 12():50. PubMed ID: 27933095
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Erratum: Eyestalk Ablation to Increase Ovarian Maturation in Mud Crabs.
    J Vis Exp; 2023 May; (195):. PubMed ID: 37235796
    [TBL] [Abstract][Full Text] [Related]  

  • 11. High-Throughput System for the Early Quantification of Major Architectural Traits in Olive Breeding Trials Using UAV Images and OBIA Techniques.
    de Castro AI; Rallo P; Suárez MP; Torres-Sánchez J; Casanova L; Jiménez-Brenes FM; Morales-Sillero A; Jiménez MR; López-Granados F
    Front Plant Sci; 2019; 10():1472. PubMed ID: 31803210
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Dynamic detection of three-dimensional crop phenotypes based on a consumer-grade RGB-D camera.
    Song P; Li Z; Yang M; Shao Y; Pu Z; Yang W; Zhai R
    Front Plant Sci; 2023; 14():1097725. PubMed ID: 36778701
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Development and Validation of Methodology for Estimating Potato Canopy Structure for Field Crop Phenotyping and Improved Breeding.
    de Jesus Colwell F; Souter J; Bryan GJ; Compton LJ; Boonham N; Prashar A
    Front Plant Sci; 2021; 12():612843. PubMed ID: 33643346
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Estimating Biomass and Canopy Height With LiDAR for Field Crop Breeding.
    Walter JDC; Edwards J; McDonald G; Kuchel H
    Front Plant Sci; 2019; 10():1145. PubMed ID: 31611889
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Field-measured canopy height may not be as accurate and heritable as believed: evidence from advanced 3D sensing.
    Zang J; Jin S; Zhang S; Li Q; Mu Y; Li Z; Li S; Wang X; Su Y; Jiang D
    Plant Methods; 2023 Apr; 19(1):39. PubMed ID: 37009892
    [TBL] [Abstract][Full Text] [Related]  

  • 16. High Throughput Determination of Plant Height, Ground Cover, and Above-Ground Biomass in Wheat with LiDAR.
    Jimenez-Berni JA; Deery DM; Rozas-Larraondo P; Condon ATG; Rebetzke GJ; James RA; Bovill WD; Furbank RT; Sirault XRR
    Front Plant Sci; 2018; 9():237. PubMed ID: 29535749
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Estimation of cotton canopy parameters based on unmanned aerial vehicle (UAV) oblique photography.
    Wu J; Wen S; Lan Y; Yin X; Zhang J; Ge Y
    Plant Methods; 2022 Dec; 18(1):129. PubMed ID: 36482426
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deep learning-based prediction of plant height and crown area of vegetable crops using LiDAR point cloud.
    J R; Nidamanuri RR
    Sci Rep; 2024 Jun; 14(1):14903. PubMed ID: 38942825
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Integrating multi-modal remote sensing, deep learning, and attention mechanisms for yield prediction in plant breeding experiments.
    Aviles Toledo C; Crawford MM; Tuinstra MR
    Front Plant Sci; 2024; 15():1408047. PubMed ID: 39119495
    [TBL] [Abstract][Full Text] [Related]  

  • 20. "Canopy fingerprints" for characterizing three-dimensional point cloud data of soybean canopies.
    Young TJ; Jubery TZ; Carley CN; Carroll M; Sarkar S; Singh AK; Singh A; Ganapathysubramanian B
    Front Plant Sci; 2023; 14():1141153. PubMed ID: 37063230
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.