PONE-D-24-01223Research on defect detection of bottle cap interior based on low-angle and large divergence angle vision systemPLOS ONE

Dear Dr. Li,

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Alessandro Bruno, Ph.D.

Academic Editor

PLOS ONE

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Additional Editor Comments:

Dear Authors,

Your manuscript shows scientific soundness with some exhaustive experimental campaigns.

However, I recommend your paper for a minor revision round as for you to address some minor issues.

You're invited to deal with all the reviewer's suggestions.

Please, run a dry English language check before getting through the next step.

Sincerely,

A.B.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

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Comments to the Author

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Reviewer #1: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

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Reviewer #1: Yes

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Reviewer #1: Yes

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5. Review Comments to the Author

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Reviewer #1: Minor Revision

(1)It is important to address whether the luminous intensity of the light source has any impact on the test results, and if so, provide a thorough explanation in the manuscript.

(2)The authors may add more state-of-art computer vision & robot articles in engineering application for the integrity of the manuscript (3D vision technologies for a self-developed structural external crack damage recognition robot; Automation in Construction. Enhanced Precision in Dam Crack Width Measurement: Leveraging Advanced Lightweight Network Identification for Pixel-Level Accuracy; International Journal of Intelligent Systems.).

(3)In the experimental section, the average detection correct rate is reported as 97.3% and compared with the average accuracy results of other deep learning networks in Table 1. However, it's crucial to acknowledge that the average accuracy of the deep learning network is just one type of network evaluation index and may not be directly comparable to the average detection correct rate. This distinction should be carefully considered and appropriately addressed.

(4)The paper's detection method and algorithms represent a departure from traditional detection schemes. Therefore, it is advisable to expand the comparison with traditional detection schemes to demonstrate the improvement in the correct detection rate.

(5)Provide a clear definition of "defective caps" to ensure readers have a complete understanding of the terminology used in the study.

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Reviewer #1: No

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Research on defect detection of bottle cap interior based on low-angle and large divergence angle vision system

PONE-D-24-01223R1

Dear Dr. Li,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Alessandro Bruno, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Dear Authors,

I appreciate your efforts in dealing with the reviewer's remarks and suggestions.

I believe your paper is now ready for acceptance although there are still some typos.

Hereby, I recommend your manuscript for acceptance.

Kinde regards

Reviewers' comments: