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 *

237 related articles for article (PubMed ID: 35937335)

  • 21. Towards reducing chemical usage for weed control in agriculture using UAS imagery analysis and computer vision techniques.
    Sapkota R; Stenger J; Ostlie M; Flores P
    Sci Rep; 2023 Apr; 13(1):6548. PubMed ID: 37085558
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Novelty Detection Classifiers in Weed Mapping: Silybum marianum Detection on UAV Multispectral Images.
    Alexandridis TK; Tamouridou AA; Pantazi XE; Lagopodi AL; Kashefi J; Ovakoglou G; Polychronos V; Moshou D
    Sensors (Basel); 2017 Sep; 17(9):. PubMed ID: 28862663
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Applications of Unmanned Aerial Vehicle Based Imagery in Turfgrass Field Trials.
    Zhang J; Virk S; Porter W; Kenworthy K; Sullivan D; Schwartz B
    Front Plant Sci; 2019; 10():279. PubMed ID: 30930917
    [TBL] [Abstract][Full Text] [Related]  

  • 24. High-Throughput Phenotyping of Fire Blight Disease Symptoms Using Sensing Techniques in Apple.
    Jarolmasjed S; Sankaran S; Marzougui A; Kostick S; Si Y; Quirós Vargas JJ; Evans K
    Front Plant Sci; 2019; 10():576. PubMed ID: 31134116
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Combining UAV-RGB high-throughput field phenotyping and genome-wide association study to reveal genetic variation of rice germplasms in dynamic response to drought stress.
    Jiang Z; Tu H; Bai B; Yang C; Zhao B; Guo Z; Liu Q; Zhao H; Yang W; Xiong L; Zhang J
    New Phytol; 2021 Oct; 232(1):440-455. PubMed ID: 34165797
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Estimation of Peanut Leaf Area Index from Unmanned Aerial Vehicle Multispectral Images.
    Qi H; Zhu B; Wu Z; Liang Y; Li J; Wang L; Chen T; Lan Y; Zhang L
    Sensors (Basel); 2020 Nov; 20(23):. PubMed ID: 33255612
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Multispectral remote sensing for accurate acquisition of rice phenotypes: Impacts of radiometric calibration and unmanned aerial vehicle flying altitudes.
    Luo S; Jiang X; Yang K; Li Y; Fang S
    Front Plant Sci; 2022; 13():958106. PubMed ID: 36035659
    [TBL] [Abstract][Full Text] [Related]  

  • 28. 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]  

  • 29. Multi-Modal Deep Learning for Weeds Detection in Wheat Field Based on RGB-D Images.
    Xu K; Zhu Y; Cao W; Jiang X; Jiang Z; Li S; Ni J
    Front Plant Sci; 2021; 12():732968. PubMed ID: 34804085
    [TBL] [Abstract][Full Text] [Related]  

  • 30. A New Vegetation Segmentation Approach for Cropped Fields Based on Threshold Detection from Hue Histograms.
    Hassanein M; Lari Z; El-Sheimy N
    Sensors (Basel); 2018 Apr; 18(4):. PubMed ID: 29670055
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Sugarcane Nitrogen Concentration and Irrigation Level Prediction Based on UAV Multispectral Imagery.
    Li X; Ba Y; Zhang M; Nong M; Yang C; Zhang S
    Sensors (Basel); 2022 Apr; 22(7):. PubMed ID: 35408324
    [TBL] [Abstract][Full Text] [Related]  

  • 32. 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]  

  • 33. Application of unmanned aerial systems for high throughput phenotyping of large wheat breeding nurseries.
    Haghighattalab A; González Pérez L; Mondal S; Singh D; Schinstock D; Rutkoski J; Ortiz-Monasterio I; Singh RP; Goodin D; Poland J
    Plant Methods; 2016; 12():35. PubMed ID: 27347001
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Deep learning for detecting herbicide weed control spectrum in turfgrass.
    Jin X; Bagavathiannan M; Maity A; Chen Y; Yu J
    Plant Methods; 2022 Jul; 18(1):94. PubMed ID: 35879797
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Identifying rice field weeds from unmanned aerial vehicle remote sensing imagery using deep learning.
    Guo Z; Cai D; Zhou Y; Xu T; Yu F
    Plant Methods; 2024 Jul; 20(1):105. PubMed ID: 39014411
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Automatic UAV-based detection of Cynodon dactylon for site-specific vineyard management.
    Jiménez-Brenes FM; López-Granados F; Torres-Sánchez J; Peña JM; Ramírez P; Castillejo-González IL; de Castro AI
    PLoS One; 2019; 14(6):e0218132. PubMed ID: 31185068
    [TBL] [Abstract][Full Text] [Related]  

  • 37. A survey on deep learning-based identification of plant and crop diseases from UAV-based aerial images.
    Bouguettaya A; Zarzour H; Kechida A; Taberkit AM
    Cluster Comput; 2023; 26(2):1297-1317. PubMed ID: 35968221
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Spatio-temporal mapping of leaf area index in rice: spectral indices and multi-scale texture comparison derived from different sensors.
    Li C; Teng X; Tan Y; Zhang Y; Zhang H; Xiao D; Luo S
    Front Plant Sci; 2024; 15():1445490. PubMed ID: 39309178
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Development of a Light-Weight Unmanned Aerial Vehicle for Precision Agriculture.
    Ukaegbu UF; Tartibu LK; Okwu MO; Olayode IO
    Sensors (Basel); 2021 Jun; 21(13):. PubMed ID: 34203187
    [TBL] [Abstract][Full Text] [Related]  

  • 40. High-Throughput Phenotyping of Bioethanol Potential in Cereals Using UAV-Based Multi-Spectral Imagery.
    Ostos-Garrido FJ; de Castro AI; Torres-Sánchez J; Pistón F; Peña JM
    Front Plant Sci; 2019; 10():948. PubMed ID: 31396251
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 12.