Research on Tea Trees Germination Density Detection Based on Improved YOLOv5

Round 1

Reviewer 1 Report

This research is about using YOLOv5 on tea tree tea bud identification and germination density, however:

1. A general framework for buds detection, including labeling the tea bud, training, image enhancement, and germination density calculation not so clear.

2. What is 4-mosaic and 9-mosaic for image enhancement method?

3. In the discussion, please add a comparison table for further explanation.

4. Abbreviation: what are CBAM, CNN, YOLO, FCN, and other terms in upper case?

Author Response

Dear Reviewer:

    Thanks for your comments concerning our manuscript entitled "Research on tea trees germination density detection based on Improved YOLOv5". Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our research. We have studied comments carefully and have made a correction which we hope meets with approval. 

    We appreciate for reviewer’s warm work earnestly and hope that the correction will meet with approval. The main corrections in the paper and the responses to the reviewer comments are in the attachment.

    Thank you very much again.

Best wishes,

All authors

Author Response File: Author Response.pdf

Reviewer 2 Report

Dear Authors:

   His article: "Research on tea trees germination density detection based on Improved YOLOv5" presents an alternative to detecting tea buds using digital imaging and deep learning. The structure of the article is adequate, however, I advise a detailed review of the writing by a native English speaker. About the appendix, I believe that the images presented here should be better discussed in the text, mainly in the discussions.

   I presented 26 observations of minor importance that can be consulted directly in the digital file. Basically, they are requests for wording improvement and text/number formatting. In order to improve the writing of your article, I request your attention to the following topics:

1) Mention the type of images used in the abstract.

2) Line 47: “The technology of quick access to tea garden information is the core technology of refined tea industry, and the basis for the rapid development of refined tea industry, and it has become a bottleneck problem restricting the development of refined tea industry. ” What's a refined tea industry? More details about this. Improve the wording as the text is confusing.

3) Present the objectives of the study at the end of chapter 1

4) Lines 155 to 165: detail the acquisition of images. The wording is confusing and the methodology for collecting the images is not clear.

5) Specify the applications and respective libraries used.

6) Detail the steps related to image processing. It would be interesting to present a flowchart of the work steps;

7) Table 5: highlight the best results by formatting the text in bold.

8) Line 371: “has a serious phenomenon of repeated detection.” Explain this issue better in terms of a target being detected more than once. What would be the alternative to avoid this multiple detections?

9) It would be interesting to compare the results you obtained with those obtained by the authors mentioned in the literature review. This could be implemented in Chapter 4.

10) Revise the conclusions so that they respond to the objectives of the work. Results were repeated. In general, the conclusions must respond to the objectives proposed for the work.

I end my review by congratulating them on the work done.

 

Respectfully,

Comments for author File: Comments.pdf

Author Response

Dear Reviewer:

    Thanks for your comments concerning our manuscript entitled "Research on tea trees germination density detection based on Improved YOLOv5". Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our research. We have studied comments carefully and have made a correction which we hope meets with approval. 

    We appreciate for reviewer’s warm work earnestly and hope that the correction will meet with approval. The main corrections in the paper and the responses to the reviewer comments are in the attachment.

    Thank you very much again.

Best wishes,

All authors

Author Response File: Author Response.pdf

Reviewer 3 Report

Dear Authors,

Please see my comments in the attached file.

Regards

Comments for author File: Comments.pdf

Author Response

Dear Reviewer:

    Thanks for your comments concerning our manuscript entitled "Research on tea trees germination density detection based on Improved YOLOv5". Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our research. We have studied comments carefully and have made a correction which we hope meets with approval. 

    We appreciate for reviewer’s warm work earnestly and hope that the correction will meet with approval. The main corrections in the paper and the responses to the reviewer comments are in the attachment.

    Thank you very much again.

Best wishes,

All authors

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Dear Authors

    The second version of your article applied or justified my suggestions. The reading of the article is fluid and the understanding of the experiment performed and the results obtained was improved.

     I request your attention to:

1) Reposition Figure 1 in Chapter 2

2) Figure 3 is incomplete.

Thank you for sending the cover Letter that helped in my review work.

 

Congratulations.

Reviewer 3 Report

Dear Authors,

Thank you for taking my comments into account.

Regards