BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

221 related articles for article (PubMed ID: 29568319)

  • 1. Wheat ear counting in-field conditions: high throughput and low-cost approach using RGB images.
    Fernandez-Gallego JA; Kefauver SC; Gutiérrez NA; Nieto-Taladriz MT; Araus JL
    Plant Methods; 2018; 14():22. PubMed ID: 29568319
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images.
    Fernandez-Gallego JA; Buchaillot ML; Gracia-Romero A; Vatter T; Diaz OV; Aparicio Gutiérrez N; Nieto-Taladriz MT; Kerfal S; Serret MD; Araus JL; Kefauver SC
    J Vis Exp; 2019 Feb; (144):. PubMed ID: 30774118
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Automatic wheat ear counting using machine learning based on RGB UAV imagery.
    Fernandez-Gallego JA; Lootens P; Borra-Serrano I; Derycke V; Haesaert G; Roldán-Ruiz I; Araus JL; Kefauver SC
    Plant J; 2020 Aug; 103(4):1603-1613. PubMed ID: 32369641
    [TBL] [Abstract][Full Text] [Related]  

  • 4.
    Sadeghi-Tehran P; Virlet N; Ampe EM; Reyns P; Hawkesford MJ
    Front Plant Sci; 2019; 10():1176. PubMed ID: 31616456
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Automatic kernel counting on maize ear using RGB images.
    Wu D; Cai Z; Han J; Qin H
    Plant Methods; 2020; 16():79. PubMed ID: 32518581
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Wheat ear counting using K-means clustering segmentation and convolutional neural network.
    Xu X; Li H; Yin F; Xi L; Qiao H; Ma Z; Shen S; Jiang B; Ma X
    Plant Methods; 2020; 16():106. PubMed ID: 32782453
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Segmentation and counting of wheat spike grains based on deep learning and textural feature.
    Xu X; Geng Q; Gao F; Xiong D; Qiao H; Ma X
    Plant Methods; 2023 Aug; 19(1):77. PubMed ID: 37528413
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. Wheat Ears Counting in Field Conditions Based on Multi-Feature Optimization and TWSVM.
    Zhou C; Liang D; Yang X; Yang H; Yue J; Yang G
    Front Plant Sci; 2018; 9():1024. PubMed ID: 30057587
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Triticale field phenotyping using RGB camera for ear counting and yield estimation.
    Stefański P; Ullah S; Matysik P; Rybka K
    J Appl Genet; 2024 May; 65(2):271-281. PubMed ID: 38353850
    [TBL] [Abstract][Full Text] [Related]  

  • 11. An automatic method for counting wheat tiller number in the field with terrestrial LiDAR.
    Fang Y; Qiu X; Guo T; Wang Y; Cheng T; Zhu Y; Chen Q; Cao W; Yao X; Niu Q; Hu Y; Gui L
    Plant Methods; 2020; 16():132. PubMed ID: 33005214
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Comparison of two novel methods for counting wheat ears in the field with terrestrial LiDAR.
    Gu Y; Ai H; Guo T; Liu P; Wang Y; Zheng H; Cheng T; Zhu Y; Cao W; Yao X
    Plant Methods; 2023 Nov; 19(1):134. PubMed ID: 38007501
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Source-Sink Dynamics in Field-Grown Durum Wheat Under Contrasting Nitrogen Supplies: Key Role of Non-Foliar Organs During Grain Filling.
    Martínez-Peña R; Schlereth A; Höhne M; Encke B; Morcuende R; Nieto-Taladriz MT; Araus JL; Aparicio N; Vicente R
    Front Plant Sci; 2022; 13():869680. PubMed ID: 35574116
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Automatic Detection and Counting of Wheat Spikelet Using Semi-Automatic Labeling and Deep Learning.
    Qiu R; He Y; Zhang M
    Front Plant Sci; 2022; 13():872555. PubMed ID: 35707612
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Winter wheat ear counting based on improved YOLOv7x and Kalman filter tracking algorithm with video streaming.
    Xu X; Zhou L; Yu H; Sun G; Fei S; Zhu J; Ma Y
    Front Plant Sci; 2024; 15():1346182. PubMed ID: 38952848
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Performance of the Two-Source Energy Balance (TSEB) Model as a Tool for Monitoring the Response of Durum Wheat to Drought by High-Throughput Field Phenotyping.
    Gómez-Candón D; Bellvert J; Royo C
    Front Plant Sci; 2021; 12():658357. PubMed ID: 33936143
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Evaluating Maize Genotype Performance under Low Nitrogen Conditions Using RGB UAV Phenotyping Techniques.
    Buchaillot ML; Gracia-Romero A; Vergara-Diaz O; Zaman-Allah MA; Tarekegne A; Cairns JE; Prasanna BM; Araus JL; Kefauver SC
    Sensors (Basel); 2019 Apr; 19(8):. PubMed ID: 30995754
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Research on the Method of Counting Wheat Ears via Video Based on Improved YOLOv7 and DeepSort.
    Wu T; Zhong S; Chen H; Geng X
    Sensors (Basel); 2023 May; 23(10):. PubMed ID: 37430792
    [TBL] [Abstract][Full Text] [Related]  

  • 20. TasselNetV2+: A Fast Implementation for High-Throughput Plant Counting From High-Resolution RGB Imagery.
    Lu H; Cao Z
    Front Plant Sci; 2020; 11():541960. PubMed ID: 33365037
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.