PONE-D-21-28703MaskID: an effective deep-learning-based algorithm for dense rebar countingPLOS ONE

Dear Dr. Chen,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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We look forward to receiving your revised manuscript.

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Humaira Nisar

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The manuscript has presented a deep learning-based method for dense rebar counting. The manuscript is well eligible for publication because of the following reasons:

1. The case study and literature are well documented and drafted with a suitable English language.

2. The performance of the proposed method is accurate and outperformed the state-of-the-art methods.

Therefore, I would like to recommend the manuscript for acceptance in its present form.

Reviewer #2: This paper proposes MaskID, an innovative counting method based on deep learning and heuristic strategies. First, a sliced version of the Mask region-based convolutional neural network (R-CNN) was designed to obtain the segmentation results. Their extensive experimental results demonstrated that their approach reaches a high accuracy.

The proposed system is very interesting and quite straight-forward, however, there are still many important issues that should be addressed before final publication.

1. Authors may revise the abstract to elaborate more on problem statement and their findings and contributions.

2. Authors may elaborate more on the novelty of their work. How it contributes to the literature. In page 2, the authors write, "The two main principles of the approach are as follows." I don't see the novelty in the MaskID algorithm used. If no one has proposed before a method like the proposed algorithm, this claim should be highlighted much more. Else, it should be indicated who has done this, and it should be indicated what the innovations of the current paper are. Furthermore, briefly describe the major contributions in bullet form, just before the organization paragraph.

3. Introduction can be improved by having four clear and concise subsections on motivation of your research; background and related works; list of key contributions; and organization of the paper.

4. A comparative literature review may require identifying the problem/ research gap in Section "Materials and Methods". A few of the references are missing some information, may complete them critically. Provided references are better enough. However, authors are recommended to consider more latest and related such as,

https://www.sciencedirect.com/science/article/abs/pii/S1047320321001711

https://www.sciencedirect.com/science/article/abs/pii/S1389128619306978

https://ieeexplore.ieee.org/abstract/document/8606255.

5. What are the shortcomings of the algorithm and what is the room for improvement? I suggest adding a brief description in the conclusion section.

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6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

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PONE-D-21-28703R1MaskID: an effective deep-learning-based algorithm for dense rebar countingPLOS ONE

Dear Dr. Chen,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

1) Section- Datasets: As mentioned by the authors 2 datasets have been used, it will be advisable if sample images from the 2 datasets should be shown to get an overview of the type of images. The first dataset has 200 images, but for the 2nd dataset, it is not clear, how many images are there. The results are only tabulated in the form of Table 2, using F1 score. The division of the datasets into training/validation and testing is not given. Nor the training and testing accuracy is mentioned. These parameters should be mentioned in the manuscript.

2) it looks like the combined results from the 2 datasets are given, which means that the 2 datasets were combined for the analysis, or dataset 2 was only used for testing and dataset 1 for training? Need to explain

3) In addition to the F-1 score it is advisable to include the values for precision and recall.

4) The details of the model should also be included.

5) Table 2 compares the result of the proposed algorithm with the state of the art. Are all these methods use the same datasets?

6) The references are a bit confusing, Ref 9 and Ref 21 are the same. It is mentioned as Retina Net, in which a dense detector is designed and named as retina NET. IT is not clear if the same dataset is used, then how to justify the results in Table 2.

7) Similar to above, ref 4 and Ref 22 are the same.

8) for table 2, if the same dataset is not used then the comparisons are not meaningful, it will be better if the authors give a detailed table in which they include the type of dataset the no of images, and results to get an overview of what is happening.

9)There are some spelling and grammatical mistakes that should be corrected. For example, line 33, should be scene.... line 85 novelty----novel.

Please submit your revised manuscript by Jul 14 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Humaira Nisar

Academic Editor

PLOS ONE

Additional Editor Comments:

Thank you for revising the manuscript.

I have the following comments:

1) Section- Datasets: As mentioned by the authors 2 datasets have been used, it will be advisable if sample images from the 2 datasets should be shown to get an overview of the type of images. The first dataset has 200 images, but for the 2nd dataset, it is not clear, how many images are there. The results are only tabulated in the form of Table 2, using F1 score. The division of the datasets into training/validation and testing is not given. Nor the training and testing accuracy is mentioned. These parameters should be mentioned in the manuscript.

2) it looks like the combined results from the 2 datasets are given, which means that the 2 datasets were combined for the analysis, or dataset 2 was only used for testing and dataset 1 for training? Need to explain

3) In addition to the F-1 score it is advisable to include the values for precision and recall.

4) The details of the model should also be included.

5) Table 2 compares the result of the proposed algorithm with the state of the art. Are all these methods use the same datasets?

6) The references are a bit confusing, Ref 9 and Ref 21 are the same. It is mentioned as Retina Net, in which a dense detector is designed and named as retina NET. IT is not clear if the same dataset is used, then how to justify the results in Table 2.

7) Similar to above, ref 4 and Ref 22 are the same.

8) for table 2, if the same dataset is not used then the comparisons are not meaningful, it will be better if the authors give a detailed table in which they include the type of dataset the no of images, and results to get an overview of what is happening.

There are some spelling and grammatical mistakes that should be corrected. For example, line 33, should be scene.... line 85 novelty----novel.

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

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The updates in the manuscript are satisfactory and the case study is suitable for the publication. I would like to recommend it for acceptance.

Reviewer #2: The revised manuscript is satisfactory and can be beneficial to readers. Therefore, I would like to recommend the publication.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

MaskID: an effective deep-learning-based algorithm for dense rebar counting

PONE-D-21-28703R2

Dear Dr. Chen,

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.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Humaira Nisar

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments: