152 related articles for article (PubMed ID: 31849057)
1. Identification of heat damage in imported soybeans based on hyperspectral imaging technology.
Liu Y; Li M; Wang S; Wu T; Jiang W; Liu Z
J Sci Food Agric; 2020 Mar; 100(4):1775-1786. PubMed ID: 31849057
[TBL] [Abstract][Full Text] [Related]
2. Nondestructive Classification of Soybean Seed Varieties by Hyperspectral Imaging and Ensemble Machine Learning Algorithms.
Wei Y; Li X; Pan X; Li L
Sensors (Basel); 2020 Dec; 20(23):. PubMed ID: 33297289
[TBL] [Abstract][Full Text] [Related]
3. Hyperspectral imaging technology combined with deep forest model to identify frost-damaged rice seeds.
Zhang L; Sun H; Rao Z; Ji H
Spectrochim Acta A Mol Biomol Spectrosc; 2020 Mar; 229():117973. PubMed ID: 31887678
[TBL] [Abstract][Full Text] [Related]
4. Random Forest (RF) Wrappers for Waveband Selection and Classification of Hyperspectral Data.
Poona NK; van Niekerk A; Nadel RL; Ismail R
Appl Spectrosc; 2016 Feb; 70(2):322-33. PubMed ID: 26903567
[TBL] [Abstract][Full Text] [Related]
5. Rapid and nondestructive watermelon (Citrullus lanatus) seed viability detection based on visible near-infrared hyperspectral imaging technology and machine learning algorithms.
Sun J; Nirere A; Dusabe KD; Yuhao Z; Adrien G
J Food Sci; 2024 Jul; 89(7):4403-4418. PubMed ID: 38957090
[TBL] [Abstract][Full Text] [Related]
6. Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean stems.
Nagasubramanian K; Jones S; Sarkar S; Singh AK; Singh A; Ganapathysubramanian B
Plant Methods; 2018; 14():86. PubMed ID: 30305840
[TBL] [Abstract][Full Text] [Related]
7. Assessing crop damage from dicamba on non-dicamba-tolerant soybean by hyperspectral imaging through machine learning.
Zhang J; Huang Y; Reddy KN; Wang B
Pest Manag Sci; 2019 Dec; 75(12):3260-3272. PubMed ID: 31006969
[TBL] [Abstract][Full Text] [Related]
8. [Variety recognition of Chinese cabbage seeds by hyperspectral imaging combined with machine learning].
Cheng SX; Kong WW; Zhang C; Liu F; He Y
Guang Pu Xue Yu Guang Pu Fen Xi; 2014 Sep; 34(9):2519-22. PubMed ID: 25532356
[TBL] [Abstract][Full Text] [Related]
9. Nondestructive Classification of Maize Moldy Seeds by Hyperspectral Imaging and Optimal Machine Learning Algorithms.
Hu Y; Wang Z; Li X; Li L; Wang X; Wei Y
Sensors (Basel); 2022 Aug; 22(16):. PubMed ID: 36015825
[TBL] [Abstract][Full Text] [Related]
10. Application of hyperspectral imaging technology for rapid identification of
Liu Y; Qiao F; Wang S; Wang R; Xu L
RSC Adv; 2021 Oct; 11(54):33939-33951. PubMed ID: 35497300
[TBL] [Abstract][Full Text] [Related]
11. Rapid and Nondestructive Measurement of Rice Seed Vitality of Different Years Using Near-Infrared Hyperspectral Imaging.
He X; Feng X; Sun D; Liu F; Bao Y; He Y
Molecules; 2019 Jun; 24(12):. PubMed ID: 31207950
[TBL] [Abstract][Full Text] [Related]
12. Cotton seed cultivar identification based on the fusion of spectral and textural features.
Liu X; Guo P; Xu Q; Du W
PLoS One; 2024; 19(5):e0303219. PubMed ID: 38805455
[TBL] [Abstract][Full Text] [Related]
13. NIR Hyperspectral Imaging Technology Combined with Multivariate Methods to Study the Residues of Different Concentrations of Omethoate on Wheat Grain Surface.
Zhang L; Rao Z; Ji H
Sensors (Basel); 2019 Jul; 19(14):. PubMed ID: 31319577
[TBL] [Abstract][Full Text] [Related]
14. Rapid Measurement of Soybean Seed Viability Using Kernel-Based Multispectral Image Analysis.
Baek I; Kusumaningrum D; Kandpal LM; Lohumi S; Mo C; Kim MS; Cho BK
Sensors (Basel); 2019 Jan; 19(2):. PubMed ID: 30641923
[TBL] [Abstract][Full Text] [Related]
15. Identification of the interference spectra of edible oil samples based on neighborhood rough set attribute reduction.
Xu S; Wu W; Gong C; Dong J; Qiao C
Appl Opt; 2023 Feb; 62(6):1537-1546. PubMed ID: 36821315
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Hyperspectral Imaging for Identification of an Invasive Plant
Huang Y; Li J; Yang R; Wang F; Li Y; Zhang S; Wan F; Qiao X; Qian W
Front Plant Sci; 2021; 12():626516. PubMed ID: 33995432
[TBL] [Abstract][Full Text] [Related]
18. [Identification of varieties of black bean using ground based hyperspectral imaging].
Zhang C; Liu F; Zhang HL; Kong WW; He Y
Guang Pu Xue Yu Guang Pu Fen Xi; 2014 Mar; 34(3):746-50. PubMed ID: 25208405
[TBL] [Abstract][Full Text] [Related]
19. [Fast Identification of Transgenic Soybean Varieties Based Near Infrared Hyperspectral Imaging Technology].
Wang HL; Yang XD; Zhang C; Guo DQ; Bao YD; He Y; Liu F
Guang Pu Xue Yu Guang Pu Fen Xi; 2016 Jun; 36(6):1843-7. PubMed ID: 30052403
[TBL] [Abstract][Full Text] [Related]
20. [Detection of Hawthorn Fruit Defects Using Hyperspectral Imaging].
Liu DH; Zhang SJ; Wang B; Yu KQ; Zhao YR; He Y
Guang Pu Xue Yu Guang Pu Fen Xi; 2015 Nov; 35(11):3167-71. PubMed ID: 26978929
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
