BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

158 related articles for article (PubMed ID: 33372635)

  • 1. DeepFlower: a deep learning-based approach to characterize flowering patterns of cotton plants in the field.
    Jiang Y; Li C; Xu R; Sun S; Robertson JS; Paterson AH
    Plant Methods; 2020 Dec; 16(1):156. PubMed ID: 33372635
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Aerial Images and Convolutional Neural Network for Cotton Bloom Detection.
    Xu R; Li C; Paterson AH; Jiang Y; Sun S; Robertson JS
    Front Plant Sci; 2017; 8():2235. PubMed ID: 29503653
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Erratum: High-Throughput Identification of Resistance to Pseudomonas syringae pv. Tomato in Tomato using Seedling Flood Assay.
    J Vis Exp; 2023 Oct; (200):. PubMed ID: 37851522
    [TBL] [Abstract][Full Text] [Related]  

  • 5. High-throughput phenotyping with deep learning gives insight into the genetic architecture of flowering time in wheat.
    Wang X; Xuan H; Evers B; Shrestha S; Pless R; Poland J
    Gigascience; 2019 Nov; 8(11):. PubMed ID: 31742599
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Supervised and Weakly Supervised Deep Learning for Segmentation and Counting of Cotton Bolls Using Proximal Imagery.
    Adke S; Li C; Rasheed KM; Maier FW
    Sensors (Basel); 2022 May; 22(10):. PubMed ID: 35632096
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A novel approach for estimating the flowering rate of litchi based on deep learning and UAV images.
    Lin P; Li D; Jia Y; Chen Y; Huang G; Elkhouchlaa H; Yao Z; Zhou Z; Zhou H; Li J; Lu H
    Front Plant Sci; 2022; 13():966639. PubMed ID: 36092399
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Multispectral imaging and unmanned aerial systems for cotton plant phenotyping.
    Xu R; Li C; Paterson AH
    PLoS One; 2019; 14(2):e0205083. PubMed ID: 30811435
    [TBL] [Abstract][Full Text] [Related]  

  • 9. DeepSeedling: deep convolutional network and Kalman filter for plant seedling detection and counting in the field.
    Jiang Y; Li C; Paterson AH; Robertson JS
    Plant Methods; 2019; 15():141. PubMed ID: 31768186
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Image-Based Phenotyping of Flowering Intensity in Cool-Season Crops.
    Zhang C; Craine WA; McGee RJ; Vandemark GJ; Davis JB; Brown J; Hulbert SH; Sankaran S
    Sensors (Basel); 2020 Mar; 20(5):. PubMed ID: 32155830
    [TBL] [Abstract][Full Text] [Related]  

  • 11. HairNet: a deep learning model to score leaf hairiness, a key phenotype for cotton fibre yield, value and insect resistance.
    Rolland V; Farazi MR; Conaty WC; Cameron D; Liu S; Petersson L; Stiller WN
    Plant Methods; 2022 Jan; 18(1):8. PubMed ID: 35042523
    [TBL] [Abstract][Full Text] [Related]  

  • 12. High-resolution temporal dynamic transcriptome landscape reveals a GhCAL-mediated flowering regulatory pathway in cotton (Gossypium hirsutum L.).
    Cheng S; Chen P; Su Z; Ma L; Hao P; Zhang J; Ma Q; Liu G; Liu J; Wang H; Wei H; Yu S
    Plant Biotechnol J; 2021 Jan; 19(1):153-166. PubMed ID: 32654381
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Molecular evolution and phylogenetic analysis of eight COL superfamily genes in group I related to photoperiodic regulation of flowering time in wild and domesticated cotton (Gossypium) species.
    Zhang R; Ding J; Liu C; Cai C; Zhou B; Zhang T; Guo W
    PLoS One; 2015; 10(2):e0118669. PubMed ID: 25710777
    [TBL] [Abstract][Full Text] [Related]  

  • 15. GPhenoVision: A Ground Mobile System with Multi-modal Imaging for Field-Based High Throughput Phenotyping of Cotton.
    Jiang Y; Li C; Robertson JS; Sun S; Xu R; Paterson AH
    Sci Rep; 2018 Jan; 8(1):1213. PubMed ID: 29352136
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. Promoting flowering, lateral shoot outgrowth, leaf development, and flower abscission in tobacco plants overexpressing cotton FLOWERING LOCUS T (FT)-like gene GhFT1.
    Li C; Zhang Y; Zhang K; Guo D; Cui B; Wang X; Huang X
    Front Plant Sci; 2015; 6():454. PubMed ID: 26136765
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Automated color detection in orchids using color labels and deep learning.
    Apriyanti DH; Spreeuwers LJ; Lucas PJF; Veldhuis RNJ
    PLoS One; 2021; 16(10):e0259036. PubMed ID: 34705870
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Mechanisms and function of flower and inflorescence reversion.
    Tooke F; Ordidge M; Chiurugwi T; Battey N
    J Exp Bot; 2005 Oct; 56(420):2587-99. PubMed ID: 16131510
    [TBL] [Abstract][Full Text] [Related]  

  • 20. On the objectivity, reliability, and validity of deep learning enabled bioimage analyses.
    Segebarth D; Griebel M; Stein N; von Collenberg CR; Martin C; Fiedler D; Comeras LB; Sah A; Schoeffler V; Lüffe T; Dürr A; Gupta R; Sasi M; Lillesaar C; Lange MD; Tasan RO; Singewald N; Pape HC; Flath CM; Blum R
    Elife; 2020 Oct; 9():. PubMed ID: 33074102
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.