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Estimation of Leaf Nitrogen Content in Wheat Based on Fusion of Spectral Features and Deep Features from Near Infrared Hyperspectral Imagery.
Yang B, Ma J, Yao X, Cao W, Zhu Y. Yang B, et al. Sensors (Basel). 2021 Jan 17;21(2):613. doi: 10.3390/s21020613. Sensors (Basel). 2021. PMID: 33477350 Free PMC article.
In particular, the estimation accuracy of the GBDT model is the best (R(2) = 0.975 for calibration set, R(2) = 0.861 for validation set). ...
In particular, the estimation accuracy of the GBDT model is the best (R(2) = 0.975 for calibration set, R(2) = 0.861 for valid …
Estimation Method of Soluble Solid Content in Peach Based on Deep Features of Hyperspectral Imagery.
Yang B, Gao Y, Yan Q, Qi L, Zhu Y, Wang B. Yang B, et al. Sensors (Basel). 2020 Sep 4;20(18):5021. doi: 10.3390/s20185021. Sensors (Basel). 2020. PMID: 32899646 Free PMC article.
In addition, the SAE-RF model based on the 1237-650-310-130 network structure has the best prediction effect (R(2) = 0.9184, RMSE = 0.6693). Our research shows that the proposed method can improve the estimation accuracy of the soluble solid content of fresh peaches, which …
In addition, the SAE-RF model based on the 1237-650-310-130 network structure has the best prediction effect (R(2) = 0.9184, RMSE = 0 …
Cross-Category Tea Polyphenols Evaluation Model Based on Feature Fusion of Electronic Nose and Hyperspectral Imagery.
Yang B, Qi L, Wang M, Hussain S, Wang H, Wang B, Ning J. Yang B, et al. Sensors (Basel). 2019 Dec 20;20(1):50. doi: 10.3390/s20010050. Sensors (Basel). 2019. PMID: 31861804 Free PMC article.
Whether based on all original features or optimized features, the performance of XGBoost is the best among the three regression algorithms (R(2) = 0.998, RMSE = 0.434). Results indicate that the proposed method in this study can improve the estimation accuracy of tea polyp …
Whether based on all original features or optimized features, the performance of XGBoost is the best among the three regression algorithms ( …
Evaluation of Aboveground Nitrogen Content of Winter Wheat Using Digital Imagery of Unmanned Aerial Vehicles.
Yang B, Wang M, Sha Z, Wang B, Chen J, Yao X, Cheng T, Cao W, Zhu Y. Yang B, et al. Sensors (Basel). 2019 Oct 12;19(20):4416. doi: 10.3390/s19204416. Sensors (Basel). 2019. PMID: 31614815 Free PMC article.
The results showed that the accuracy of the model based on the spectral-spatial feature by combining VIs and WFs was higher than that of VIs or WF indices alone. The performance of PSO-SVR was the best (R(2) = 0.9025, root mean square error (RMSE) = 0.3287) among the three …
The results showed that the accuracy of the model based on the spectral-spatial feature by combining VIs and WFs was higher than that of VIs …