BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

163 related articles for article (PubMed ID: 38400222)

  • 1. Monitoring of Antarctica's Fragile Vegetation Using Drone-Based Remote Sensing, Multispectral Imagery and AI.
    Raniga D; Amarasingam N; Sandino J; Doshi A; Barthelemy J; Randall K; Robinson SA; Gonzalez F; Bollard B
    Sensors (Basel); 2024 Feb; 24(4):. PubMed ID: 38400222
    [TBL] [Abstract][Full Text] [Related]  

  • 2. ShetlandsUAVmetry: unmanned aerial vehicle-based photogrammetric dataset for Antarctic environmental research.
    Román A; Navarro G; Tovar-Sánchez A; Zarandona P; Roque-Atienza D; Barbero L
    Sci Data; 2024 Feb; 11(1):202. PubMed ID: 38355698
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A comparative study of remote sensing classification methods for monitoring and assessing desert vegetation using a UAV-based multispectral sensor.
    Al-Ali ZM; Abdullah MM; Asadalla NB; Gholoum M
    Environ Monit Assess; 2020 May; 192(6):389. PubMed ID: 32447581
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Automated mapping of
    Galuszynski NC; Duker R; Potts AJ; Kattenborn T
    PeerJ; 2022; 10():e14219. PubMed ID: 36262418
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Monitoring recent changes of vegetation in Fildes Peninsula (King George Island, Antarctica) through satellite imagery guided by UAV surveys.
    Miranda V; Pina P; Heleno S; Vieira G; Mora C; E G R Schaefer C
    Sci Total Environ; 2020 Feb; 704():135295. PubMed ID: 31836216
    [TBL] [Abstract][Full Text] [Related]  

  • 6. AI-PUCMDL: artificial intelligence assisted plant counting through unmanned aerial vehicles in India's mountainous regions.
    Thakur D; Srinivasan S
    Environ Monit Assess; 2024 Apr; 196(4):406. PubMed ID: 38561525
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Assessing the effectiveness of specially protected areas for conservation of Antarctica's botanical diversity.
    Hughes KA; Ireland LC; Convey P; Fleming AH
    Conserv Biol; 2016 Feb; 30(1):113-20. PubMed ID: 26205208
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Species level mapping of a seagrass bed using an unmanned aerial vehicle and deep learning technique.
    Tahara S; Sudo K; Yamakita T; Nakaoka M
    PeerJ; 2022; 10():e14017. PubMed ID: 36275465
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Above-Ground Biomass Estimation in Oats Using UAV Remote Sensing and Machine Learning.
    Sharma P; Leigh L; Chang J; Maimaitijiang M; Caffé M
    Sensors (Basel); 2022 Jan; 22(2):. PubMed ID: 35062559
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Utilizing Spectral, Structural and Textural Features for Estimating Oat Above-Ground Biomass Using UAV-Based Multispectral Data and Machine Learning.
    Dhakal R; Maimaitijiang M; Chang J; Caffe M
    Sensors (Basel); 2023 Dec; 23(24):. PubMed ID: 38139554
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Aerial Mapping of Forests Affected by Pathogens Using UAVs, Hyperspectral Sensors, and Artificial Intelligence.
    Sandino J; Pegg G; Gonzalez F; Smith G
    Sensors (Basel); 2018 Mar; 18(4):. PubMed ID: 29565822
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Are unmanned aerial vehicle-based hyperspectral imaging and machine learning advancing crop science?
    Matese A; Prince Czarnecki JM; Samiappan S; Moorhead R
    Trends Plant Sci; 2024 Feb; 29(2):196-209. PubMed ID: 37802693
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Cost benefit analysis of survey methods for assessing intertidal sediment disturbance: A bait collection case study.
    White SM; Schaefer M; Barfield P; Cantrell R; Watson GJ
    J Environ Manage; 2022 Mar; 306():114386. PubMed ID: 35030426
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Perspectives for Remote Sensing with Unmanned Aerial Vehicles in Precision Agriculture.
    Maes WH; Steppe K
    Trends Plant Sci; 2019 Feb; 24(2):152-164. PubMed ID: 30558964
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Development of Multiple UAV Collaborative Driving Systems for Improving Field Phenotyping.
    Lee HS; Shin BS; Thomasson JA; Wang T; Zhang Z; Han X
    Sensors (Basel); 2022 Feb; 22(4):. PubMed ID: 35214326
    [TBL] [Abstract][Full Text] [Related]  

  • 18. [Comparison of precision in retrieving soybean leaf area index based on multi-source remote sensing data].
    Gao L; Li CC; Wang BS; Yang Gui-jun ; Wang L; Fu K
    Ying Yong Sheng Tai Xue Bao; 2016 Jan; 27(1):191-200. PubMed ID: 27228609
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Using unmanned aerial systems and deep learning for agriculture mapping in Dubai.
    El Hoummaidi L; Larabi A; Alam K
    Heliyon; 2021 Oct; 7(10):e08154. PubMed ID: 34703924
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Real-time scene classification of unmanned aerial vehicles remote sensing image based on Modified GhostNet.
    Shen X; Wang H; Wei B; Cao J
    PLoS One; 2023; 18(6):e0286873. PubMed ID: 37285360
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.