The Application of Hyperspectral Images in the Classification of Fresh Leaves’ Maturity for Flue-Curing Tobacco
Round 1
Reviewer 1 Report
The author applied hyperspectral imaging combined with machine learnings for classing the fresh leaves' maturity. Here are some comments:
1 Please improve Figure 4, I can't get difference among the samples, maybe you can use average spectral of each stage?
2 Table2 there are only 6 samples in "Unripe" stage. Please add samples
3There are 11 filtered methods for original data, please the effective methods. (There are 7 methods with lower accuracy than original data)
4PSO select 70 or 66 important wavelenghts, too much, you just using SPA and PSO, please add other helpful selective algorithm.
Author Response
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Author Response File: Author Response.pdf
Reviewer 2 Report
This is an interesting work presenting an interesting research on the application of Hyperspectral images in the Classification of tobacco leaves. Some comments:
- Highlight all assumptions and limitations of your work.
- Conclusions should provide some lessons learnt.
- Related works section does not mention recent research efforts in related fields on classification and predicition on highly correlated and scarce sequential data. Authors are advised to refer to the following related articles to add some discussions: [1] Novel Data-Driven Models Applied to Short-Term Electric Load Forecasting, Applied Sciences, 2021 [2] Additive Ensemble Neural Network with Constrained Weighted Quantile Loss for Probabilistic Electric-Load Forecasting, sensors, 2021 [3] Plant Species Classification Based on Hyperspectral Imaging via a Lightweight Convolutional Neural Network Model. Frontiers in Plant Science. 2022 [4] Bloodstain Identification Based on Visible/Near-Infrared Hyperspectral Imaging With Convolutional Neural Network, IEEE Access, 2022 [5]Hyperspectral Image Classification Based on Expansion Convolution Network, IEEE Transactions on Geoscience and Remote Sensing , 2022
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
Comments for author File: Comments.pdf
Author Response
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Author Response File: Author Response.pdf