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 *

185 related articles for article (PubMed ID: 39119495)

  • 1. 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]  

  • 2. UAV Multisensory Data Fusion and Multi-Task Deep Learning for High-Throughput Maize Phenotyping.
    Nguyen C; Sagan V; Bhadra S; Moose S
    Sensors (Basel); 2023 Feb; 23(4):. PubMed ID: 36850425
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system.
    Kumar K; Parihar CM; Nayak HS; Sena DR; Godara S; Dhakar R; Patra K; Sarkar A; Bharadwaj S; Ghasal PC; L Meena A; Reddy KS; Das TK; Jat SL; Sharma DK; Saharawat YS; Singh U; Jat ML; Gathala MK
    Sci Rep; 2024 May; 14(1):11743. PubMed ID: 38778072
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A Multi-Modal Deep-Learning Air Quality Prediction Method Based on Multi-Station Time-Series Data and Remote-Sensing Images: Case Study of Beijing and Tianjin.
    Xia H; Chen X; Wang Z; Chen X; Dong F
    Entropy (Basel); 2024 Jan; 26(1):. PubMed ID: 38275499
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Multimodal remote sensing application for weed competition time series analysis in maize farmland ecosystems.
    Quan L; Lou Z; Lv X; Sun D; Xia F; Li H; Sun W
    J Environ Manage; 2023 Oct; 344():118376. PubMed ID: 37329583
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Prediction of End-Of-Season Tuber Yield and Tuber Set in Potatoes Using In-Season UAV-Based Hyperspectral Imagery and Machine Learning.
    Sun C; Feng L; Zhang Z; Ma Y; Crosby T; Naber M; Wang Y
    Sensors (Basel); 2020 Sep; 20(18):. PubMed ID: 32947919
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Remote sensing for field pea yield estimation: A study of multi-scale data fusion approaches in phenomics.
    Marzougui A; McGee RJ; Van Vleet S; Sankaran S
    Front Plant Sci; 2023; 14():1111575. PubMed ID: 37152173
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level.
    Jiang H; Hu H; Zhong R; Xu J; Xu J; Huang J; Wang S; Ying Y; Lin T
    Glob Chang Biol; 2020 Mar; 26(3):1754-1766. PubMed ID: 31789455
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Crop yield prediction integrating genotype and weather variables using deep learning.
    Shook J; Gangopadhyay T; Wu L; Ganapathysubramanian B; Sarkar S; Singh AK
    PLoS One; 2021; 16(6):e0252402. PubMed ID: 34138872
    [TBL] [Abstract][Full Text] [Related]  

  • 11. TrG2P: A transfer-learning-based tool integrating multi-trait data for accurate prediction of crop yield.
    Li J; Zhang D; Yang F; Zhang Q; Pan S; Zhao X; Zhang Q; Han Y; Yang J; Wang K; Zhao C
    Plant Commun; 2024 Jul; 5(7):100975. PubMed ID: 38751121
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning.
    Bellis ES; Hashem AA; Causey JL; Runkle BRK; Moreno-García B; Burns BW; Green VS; Burcham TN; Reba ML; Huang X
    Front Plant Sci; 2022; 13():716506. PubMed ID: 35401643
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Estimation of physiological genomic estimated breeding values (PGEBV) combining full hyperspectral and marker data across environments for grain yield under combined heat and drought stress in tropical maize (Zea mays L.).
    Trachsel S; Dhliwayo T; Gonzalez Perez L; Mendoza Lugo JA; Trachsel M
    PLoS One; 2019; 14(3):e0212200. PubMed ID: 30893307
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Joint Classification of Hyperspectral Images and LiDAR Data Based on Dual-Branch Transformer.
    Wang Q; Zhou B; Zhang J; Xie J; Wang Y
    Sensors (Basel); 2024 Jan; 24(3):. PubMed ID: 38339584
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics.
    Togninalli M; Wang X; Kucera T; Shrestha S; Juliana P; Mondal S; Pinto F; Govindan V; Crespo-Herrera L; Huerta-Espino J; Singh RP; Borgwardt K; Poland J
    Bioinformatics; 2023 Jun; 39(6):. PubMed ID: 37220903
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Interpretable and explainable hybrid model for daily streamflow prediction based on multi-factor drivers.
    Wan W; Zhou Y; Chen Y
    Environ Sci Pollut Res Int; 2024 May; 31(23):34588-34606. PubMed ID: 38710844
    [TBL] [Abstract][Full Text] [Related]  

  • 17. UAV-based multi-sensor data fusion and machine learning algorithm for yield prediction in wheat.
    Fei S; Hassan MA; Xiao Y; Su X; Chen Z; Cheng Q; Duan F; Chen R; Ma Y
    Precis Agric; 2023; 24(1):187-212. PubMed ID: 35967193
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Ultra-high-resolution hyperspectral imagery datasets for precision agriculture applications.
    Munipalle VK; Nelakuditi UR; C V S S MK; Nidamanuri RR
    Data Brief; 2024 Aug; 55():110649. PubMed ID: 39035837
    [TBL] [Abstract][Full Text] [Related]  

  • 19. County-Level Soybean Yield Prediction Using Deep CNN-LSTM Model.
    Sun J; Di L; Sun Z; Shen Y; Lai Z
    Sensors (Basel); 2019 Oct; 19(20):. PubMed ID: 31600963
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Predicting rice yield at pixel scale through synthetic use of crop and deep learning models with satellite data in South and North Korea.
    Jeong S; Ko J; Yeom JM
    Sci Total Environ; 2022 Jan; 802():149726. PubMed ID: 34464811
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.