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 *

124 related articles for article (PubMed ID: 34063552)

  • 1. Application of Hyperspectral Imaging and Deep Learning for Robust Prediction of Sugar and pH Levels in Wine Grape Berries.
    Gomes V; Mendes-Ferreira A; Melo-Pinto P
    Sensors (Basel); 2021 May; 21(10):. PubMed ID: 34063552
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Characterization of neural network generalization in the determination of pH and anthocyanin content of wine grape in new vintages and varieties.
    Gomes V; Fernandes A; Martins-Lopes P; Pereira L; Mendes Faia A; Melo-Pinto P
    Food Chem; 2017 Mar; 218():40-46. PubMed ID: 27719927
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Rapid Determination of Wine Grape Maturity Level from pH, Titratable Acidity, and Sugar Content Using Non-Destructive In Situ Infrared Spectroscopy and Multi-Head Attention Convolutional Neural Networks.
    Kalopesa E; Gkrimpizis T; Samarinas N; Tsakiridis NL; Zalidis GC
    Sensors (Basel); 2023 Nov; 23(23):. PubMed ID: 38067909
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Estimation of Sugar Content in Wine Grapes via In Situ VNIR-SWIR Point Spectroscopy Using Explainable Artificial Intelligence Techniques.
    Kalopesa E; Karyotis K; Tziolas N; Tsakiridis N; Samarinas N; Zalidis G
    Sensors (Basel); 2023 Jan; 23(3):. PubMed ID: 36772104
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Investigating the relationship between grape cell wall polysaccharide composition and the extractability of phenolic compounds into Shiraz wines. Part I: Vintage and ripeness effects.
    Garrido-Bañuelos G; Buica A; Schückel J; Zietsman AJJ; Willats WGT; Moore JP; Du Toit WJ
    Food Chem; 2019 Apr; 278():36-46. PubMed ID: 30583384
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Investigating a Selection of Methods for the Prediction of Total Soluble Solids Among Wine Grape Quality Characteristics Using Normalized Difference Vegetation Index Data From Proximal and Remote Sensing.
    Kasimati A; Espejo-Garcia B; Vali E; Malounas I; Fountas S
    Front Plant Sci; 2021; 12():683078. PubMed ID: 34178002
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Research on nondestructive identification of grape varieties based on EEMD-DWT and hyperspectral image.
    Xu M; Sun J; Zhou X; Tang N; Shen J; Wu X
    J Food Sci; 2021 May; 86(5):2011-2023. PubMed ID: 33885160
    [TBL] [Abstract][Full Text] [Related]  

  • 8. [Research on the sugar content measurement of grape and berries by using Vis/NIR spectroscopy technique].
    Wu GF; Huang LX; He Y
    Guang Pu Xue Yu Guang Pu Fen Xi; 2008 Sep; 28(9):2090-3. PubMed ID: 19093567
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A novel ground truth multispectral image dataset with weight, anthocyanins, and Brix index measures of grape berries tested for its utility in machine learning pipelines.
    Navarro PJ; Miller L; Díaz-Galián MV; Gila-Navarro A; Aguila DJ; Egea-Cortines M
    Gigascience; 2022 Jun; 11():. PubMed ID: 35701377
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Dataset containing spectral data from hyperspectral imaging and sugar content measurements of grapes berries in various maturity stage.
    Ryckewaert M; Héran D; Feilhes C; Prezman F; Serrano E; Courand A; Mas-Garcia S; Metz M; Bendoula R
    Data Brief; 2023 Feb; 46():108822. PubMed ID: 36582988
    [TBL] [Abstract][Full Text] [Related]  

  • 11. On-The-Go Hyperspectral Imaging Under Field Conditions and Machine Learning for the Classification of Grapevine Varieties.
    Gutiérrez S; Fernández-Novales J; Diago MP; Tardaguila J
    Front Plant Sci; 2018; 9():1102. PubMed ID: 30090110
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Discrimination of
    Wu N; Zhang C; Bai X; Du X; He Y
    Molecules; 2018 Oct; 23(11):. PubMed ID: 30384477
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A Lightweight 1-D Convolution Augmented Transformer with Metric Learning for Hyperspectral Image Classification.
    Hu X; Yang W; Wen H; Liu Y; Peng Y
    Sensors (Basel); 2021 Mar; 21(5):. PubMed ID: 33802533
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Rapid nondestructive detecting of sorghum varieties based on hyperspectral imaging and convolutional neural network.
    Bu Y; Jiang X; Tian J; Hu X; Han L; Huang D; Luo H
    J Sci Food Agric; 2023 Jun; 103(8):3970-3983. PubMed ID: 36397181
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Sugariness prediction of Syzygium samarangense using convolutional learning of hyperspectral images.
    Chen CJ; Yan YJ; Huang CC; Chien JT; Chu CT; Jang JW; Chen TC; Lin SG; Shih RS; Ou-Yang M
    Sci Rep; 2022 Feb; 12(1):2774. PubMed ID: 35177733
    [TBL] [Abstract][Full Text] [Related]  

  • 16. [Application and prospects of hyperspectral imaging and deep learning in traditional Chinese medicine in context of AI and industry 4.0].
    Yi T; Lin C; En-Ci J; Ji-Zhong Y
    Zhongguo Zhong Yao Za Zhi; 2020 Nov; 45(22):5438-5442. PubMed ID: 33350203
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Use of Visible and Short-Wave Near-Infrared Hyperspectral Imaging To Fingerprint Anthocyanins in Intact Grape Berries.
    Diago MP; Fernández-Novales J; Fernandes AM; Melo-Pinto P; Tardaguila J
    J Agric Food Chem; 2016 Oct; 64(40):7658-7666. PubMed ID: 27653674
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Hyperspectral Technique Combined With Deep Learning Algorithm for Prediction of Phenotyping Traits in Lettuce.
    Yu S; Fan J; Lu X; Wen W; Shao S; Guo X; Zhao C
    Front Plant Sci; 2022; 13():927832. PubMed ID: 35845657
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Application of Deep Learning Architectures for Accurate and Rapid Detection of Internal Mechanical Damage of Blueberry Using Hyperspectral Transmittance Data.
    Wang Z; Hu M; Zhai G
    Sensors (Basel); 2018 Apr; 18(4):. PubMed ID: 29642454
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Estimation of total soluble solids in grape berries using a hand-held NIR spectrometer under field conditions.
    Urraca R; Sanz-Garcia A; Tardaguila J; Diago MP
    J Sci Food Agric; 2016 Jul; 96(9):3007-16. PubMed ID: 26399449
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.