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 *

211 related articles for article (PubMed ID: 33123178)

  • 1. Image-Based High-Throughput Detection and Phenotype Evaluation Method for Multiple Lettuce Varieties.
    Du J; Lu X; Fan J; Qin Y; Yang X; Guo X
    Front Plant Sci; 2020; 11():563386. PubMed ID: 33123178
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Quantitative phenotyping and evaluation for lettuce leaves of multiple semantic components.
    Du J; Li B; Lu X; Yang X; Guo X; Zhao C
    Plant Methods; 2022 Apr; 18(1):54. PubMed ID: 35468831
    [TBL] [Abstract][Full Text] [Related]  

  • 3. DeepCob: precise and high-throughput analysis of maize cob geometry using deep learning with an application in genebank phenomics.
    Kienbaum L; Correa Abondano M; Blas R; Schmid K
    Plant Methods; 2021 Aug; 17(1):91. PubMed ID: 34419093
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Detection and analysis of wheat spikes using Convolutional Neural Networks.
    Hasan MM; Chopin JP; Laga H; Miklavcic SJ
    Plant Methods; 2018; 14():100. PubMed ID: 30459822
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Convolutional Neural Networks for Image-Based High-Throughput Plant Phenotyping: A Review.
    Jiang Y; Li C
    Plant Phenomics; 2020; 2020():4152816. PubMed ID: 33313554
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A Robust Automated Image-Based Phenotyping Method for Rapid Vegetative Screening of Wheat Germplasm for Nitrogen Use Efficiency.
    Nguyen GN; Maharjan P; Maphosa L; Vakani J; Thoday-Kennedy E; Kant S
    Front Plant Sci; 2019; 10():1372. PubMed ID: 31772563
    [TBL] [Abstract][Full Text] [Related]  

  • 7. High-throughput phenotyping of lateral expansion and regrowth of spaced Lolium perenne plants using on-field image analysis.
    Lootens P; Ruttink T; Rohde A; Combes D; Barre P; Roldán-Ruiz I
    Plant Methods; 2016; 12():32. PubMed ID: 27293473
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Hyperspectral Technique Combined With Deep Learning Algorithm for Prediction of Phenotyping Traits in Lettuce.
    Yu S; Fan J; Lu X; Wen W; Shao S; Guo X; Zhao C
    Front Plant Sci; 2022; 13():927832. PubMed ID: 35845657
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Computer vision and machine learning enabled soybean root phenotyping pipeline.
    Falk KG; Jubery TZ; Mirnezami SV; Parmley KA; Sarkar S; Singh A; Ganapathysubramanian B; Singh AK
    Plant Methods; 2020; 16():5. PubMed ID: 31993072
    [TBL] [Abstract][Full Text] [Related]  

  • 10. SpikeSegNet-a deep learning approach utilizing encoder-decoder network with hourglass for spike segmentation and counting in wheat plant from visual imaging.
    Misra T; Arora A; Marwaha S; Chinnusamy V; Rao AR; Jain R; Sahoo RN; Ray M; Kumar S; Raju D; Jha RR; Nigam A; Goel S
    Plant Methods; 2020; 16():40. PubMed ID: 32206080
    [TBL] [Abstract][Full Text] [Related]  

  • 11. AraDQ: an automated digital phenotyping software for quantifying disease symptoms of flood-inoculated Arabidopsis seedlings.
    Lee JH; Lee U; Yoo JH; Lee TS; Jung JH; Kim HS
    Plant Methods; 2024 Mar; 20(1):44. PubMed ID: 38493119
    [TBL] [Abstract][Full Text] [Related]  

  • 12. High-Throughput Field Plant Phenotyping: A Self-Supervised Sequential CNN Method to Segment Overlapping Plants.
    Guo X; Qiu Y; Nettleton D; Schnable PS
    Plant Phenomics; 2023; 5():0052. PubMed ID: 37213545
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Maize-IAS: a maize image analysis software using deep learning for high-throughput plant phenotyping.
    Zhou S; Chai X; Yang Z; Wang H; Yang C; Sun T
    Plant Methods; 2021 Apr; 17(1):48. PubMed ID: 33926480
    [TBL] [Abstract][Full Text] [Related]  

  • 14. High-throughput soybean seeds phenotyping with convolutional neural networks and transfer learning.
    Yang S; Zheng L; He P; Wu T; Sun S; Wang M
    Plant Methods; 2021 May; 17(1):50. PubMed ID: 33952294
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Phenomics based prediction of plant biomass and leaf area in wheat using machine learning approaches.
    Singh B; Kumar S; Elangovan A; Vasht D; Arya S; Duc NT; Swami P; Pawar GS; Raju D; Krishna H; Sathee L; Dalal M; Sahoo RN; Chinnusamy V
    Front Plant Sci; 2023; 14():1214801. PubMed ID: 37448870
    [TBL] [Abstract][Full Text] [Related]  

  • 16. PhenoTrack3D: an automatic high-throughput phenotyping pipeline to track maize organs over time.
    Daviet B; Fernandez R; Cabrera-Bosquet L; Pradal C; Fournier C
    Plant Methods; 2022 Dec; 18(1):130. PubMed ID: 36482291
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. PI-Plat: a high-resolution image-based 3D reconstruction method to estimate growth dynamics of rice inflorescence traits.
    Sandhu J; Zhu F; Paul P; Gao T; Dhatt BK; Ge Y; Staswick P; Yu H; Walia H
    Plant Methods; 2019; 15():162. PubMed ID: 31889986
    [TBL] [Abstract][Full Text] [Related]  

  • 19. TMSCNet: A three-stage multi-branch self-correcting trait estimation network for RGB and depth images of lettuce.
    Zhang Q; Zhang X; Wu Y; Li X
    Front Plant Sci; 2022; 13():982562. PubMed ID: 36119576
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Automatic monitoring of lettuce fresh weight by multi-modal fusion based deep learning.
    Lin Z; Fu R; Ren G; Zhong R; Ying Y; Lin T
    Front Plant Sci; 2022; 13():980581. PubMed ID: 36092436
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.