LBNP: Learning features between neighboring points for point cloud classification

Lei Wang; Ming Huang; Zhenqing Yang; Rui Wu; Dashi Qiu; Xingxing Xiao; Dong Li; Cai Chen

doi:10.1371/journal.pone.0314086

Peer Review History

Original SubmissionMay 16, 2024
16 Jun 2024 Decision Letter - Ayesha Maqbool, Editor PONE-D-24-19727Learning features between neighboring points for point cloud classificationPLOS ONE Dear Dr. wang, 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. The paper presents the Point Cloud Local Auxiliary Block (PLAB) and the Dual Attention Layer (DAL), enhancing feature representation in point clouds. While the experimental results are promising, the manuscript requires significant revisions. The introduction should better connect existing methods to the authors' work, highlighting innovations. Additionally, the clarity of images and detailed explanations of formulas need improvement. Finally, more recent comparison methods should be included to strengthen the research context and relevance. Please submit your revised manuscript by Jul 31 2024 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, Ayesha Maqbool, PhD Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. Please note that PLOS ONE has specific guidelines on code sharing for submissions in which author-generated code underpins the findings in the manuscript. In these cases, we expect all author-generated code to be made available without restrictions upon publication of the work. Please review our guidelines at https://journals.plos.org/plosone/s/materials-and-software-sharing#loc-sharing-code and ensure that your code is shared in a way that follows best practice and facilitates reproducibility and reuse. 3. Thank you for stating the following financial disclosure: "This study is sponsored by the BUCEA Doctor Graduate Scientific Research Ability Improvement Project(DG2024034) and National Natural Science Foundation of China (42171416)." Please state what role the funders took in the study. If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." If this statement is not correct you must amend it as needed. Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf. 4. "Thank you for stating the following in the Acknowledgments Section of your manuscript: "This study is sponsored by the BUCEA Doctor Graduate Scientific Research Ability Improvement Project(DG2024034) and National Natural Science Foundation of China (42171416)." We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form. Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows: "This study is sponsored by the BUCEA Doctor Graduate Scientific Research Ability Improvement Project(DG2024034) and National Natural Science Foundation of China (42171416)." Please include your amended statements within your cover letter; we will change the online submission form on your behalf. 5. Thank you for stating the following in your Competing Interests section: "NO authors have competing interests" Please complete your Competing Interests on the online submission form to state any Competing Interests. If you have no competing interests, please state "The authors have declared that no competing interests exist.", as detailed online in our guide for authors at http://journals.plos.org/plosone/s/submit-now This information should be included in your cover letter; we will change the online submission form on your behalf. 6. Please amend the manuscript submission data (via Edit Submission) to include authors Dr. Ming Huang, Dr. Rui Wu, Dr. Dashi Qiu, Dr. Xingxing Xiao, Dr. Dong Li, and Dr. Cai Chen. 7. Please amend your list of authors on the manuscript to ensure that each author is linked to an affiliation. Authors’ affiliations should reflect the institution where the work was done (if authors moved subsequently, you can also list the new affiliation stating “current affiliation:….” as necessary). 8. We note that Figure [1] includes an image of a [patient / participant / in the study]. As per the PLOS ONE policy (http://journals.plos.org/plosone/s/submission-guidelines#loc-human-subjects-research) on papers that include identifying, or potentially identifying, information, the individual(s) or parent(s)/guardian(s) must be informed of the terms of the PLOS open-access (CC-BY) license and provide specific permission for publication of these details under the terms of this license. Please download the Consent Form for Publication in a PLOS Journal (http://journals.plos.org/plosone/s/file?id=8ce6/plos-consent-form-english.pdf). The signed consent form should not be submitted with the manuscript, but should be securely filed in the individual's case notes. Please amend the methods section and ethics statement of the manuscript to explicitly state that the patient/participant has provided consent for publication: “The individual in this manuscript has given written informed consent (as outlined in PLOS consent form) to publish these case details”. If you are unable to obtain consent from the subject of the photograph, you will need to remove the figure and any other textual identifying information or case descriptions for this individual. [Note: HTML markup is below. Please do not edit.] 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: No Reviewer #2: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: No Reviewer #2: Yes ****** 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 ****** 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: No Reviewer #2: Yes ****** 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: This paper introduces the Point Cloud Local Auxiliary Block (PLAB), inspired by local binary pattern algorithms, to improve neighborhood feature representation in point clouds. Additionally, the Dual Attention Layer (DAL), a Transformer structure, captures both local and global features using attention score maps. Experimental results show enhanced learning of features on various point cloud datasets. The authors will publish their code and experimental logs on GitHub, promoting transparency and reproducibility. Most of the comparison methods are too outdated, especially other learning-based methods. Why modelnet40 is conduct on 4060ti, fg3d is on 3060ti? Why not both using 4060ti? In fg3d, why dcnet is better than the method proposed in this paper? The references and comparison methods are too outdated. It is now 2024, so at least try to compare the methods from 2023 to the present. Which benchmark network is this paper primarily based on? There are many typos and grammar issues in the paper. For example, “Relu”; line 226 “… and …”; There are some issues with the formatting of the paper. Eq. (4), (5) (8); The title and body of Table 1 are separated. I suggest the author use the latex template of PLOS ONE. In table 1, the “point” in the table is redundant. Most of the comparison methods are too outdated. Reviewer #2: In this paper, the author proposed a simple and effective local complement module, PLAB, which is derived from the local binary pattern image texture extraction algorithm, to establish the relationship between neighborhood points and obtain effective features. The text performs well in the chart and experimental sections, but there are some minor issues in the introduction of the work. Here are a few suggestions: 1.The percentage symbols in Equations 4, 5, 7, and 8 are misaligned. It is recommended to adjust the size of the percentage symbols to make them look more coordinated. 2.It is suggested that the author introduces more about the connection between different methods and their own work in the related work section. Explain how your method finds innovation among many methods, rather than merely listing the contents of others' work extensively. 3.It is recommended to provide more detailed explanations for the formulas in the text. 4.The images inserted in the text are mostly of insufficient clarity; it is recommended to replace them with higher-resolution images. ****** 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 ******** [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. https://doi.org/10.1371/journal.pone.0314086.r001
Revision 1
30 Aug 2024 Author Response response to editor: point 1:Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. response 1:We have carefully revised the manuscript according to the template, and if it still does not meet the requirements, we will continue to revise it. point 2:Please note that PLOS ONE has specific guidelines on code sharing for submissions in which author-generated code underpins the findings in the manuscript. In these cases, we expect all author-generated code to be made available without restrictions upon publication of the work. response 2:Our code is on other devices, and we hope to release it after the article is accepted. point 3:Please state what role the funders took in the study. If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." If this statement is not correct you must amend it as needed. Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf. response 3:We stated "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." in our cover letter. point 4:We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form. Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. response 4:We have removed the mention of fund support in the acknowledgements, so please update the fund support "BUCEA Doctor Graduate Scientific Research Ability Improvement Project(DG2024034) and National Natural Science Foundation of China (42171416).". point 5:Please complete your Competing Interests on the online submission form to state any Competing Interests. If you have no competing interests, please state "The authors have declared that no competing interests exist." response 5:We have already noted "The authors have declared that no competing interests exist." in the cover letter. Point 6: Please amend the manuscript submission data (via Edit Submission) to include authors Dr. Ming Huang, Dr. Rui Wu, Dr. Dashi Qiu, Dr. Xingxing Xiao, Dr. Dong Li, and Dr. Cai Chen. Response 6: We will amend the manuscript submission data. Point 7: Please amend your list of authors on the manuscript to ensure that each author is linked to an affiliation. Authors’ affiliations should reflect the institution where the work was done (if authors moved subsequently, you can also list the new affiliation stating “current affiliation:….” as necessary). Response 7:We have amend list of authors on the manuscript. Point 8: We note that Figure [1] includes an image of a [patient / participant / in the study]. If you are unable to obtain consent from the subject of the photograph, you will need to remove the figure and any other textual identifying information or case descriptions for this individual. Response 8: We were unable to obtain consent, so we removed Figure 1. Response to Reviewer#1: Point 1. Most of the comparison methods are too outdated, especially other learning-based methods. Response 1: Thank you for your suggestion. In fact, the writing of this manuscript was completed at the end of 2023, and the methods we compared included some classic papers as well as newer papers from 2022 and 2023, such as 3DPCT and PointConT. However, we agree with your suggestion and add some of the latest methods for comparison. Specifically refer to lines 159-165 and Table 1 of the Revised Manuscript with Track change. Point 2. Why modelnet40 is conduct on 4060ti, fg3d is on 3060ti? Why not both using 4060ti? Response 2: Thank you for your careful review. Since the experiments were conducted on different devices, we have repeated the experiments on the 4060Ti device. Specifically refer to Table 3 of the Revised Manuscript with Track change. Point 3. In fg3d, why dcnet is better than the method proposed in this paper? Response 3：Your question is well-taken. After extensive experiments, we found that many existing models perform differently on different datasets. For example, while DCNet outperformed our proposed method on the FG3D dataset, it only achieved a 92.4% overall accuracy on the ModelNet40 dataset, significantly lower than our 93.3% overall accuracy. Furthermore, while our proposed method's performance on the FG3D dataset was not the best, its results were still competitive, indicating that our method is adaptable to different datasets. Point 4. The references and comparison methods are too outdated. It is now 2024, so at least try to compare the methods from 2023 to the present. Response 4：Thank you for your suggestion. As mentioned in Point 1, the methods we compared include both classic and newer ones, and we have added new methods to the manuscript. Point 5. Which benchmark network is this paper primarily based on? Response 5：Thank you for your question. Our benchmark network is PCT, and we highlighted the issue of this oversight in the manuscript. Specifically refer to lines 403 of the Revised Manuscript with Track change. Point 6. There are many typos and grammar issues in the paper. For example, “Relu”; line 226 “… and …”; Response 6：Thank you for your suggestion. We carefully rechecked the manuscript and made corrections to spelling and grammar. Specifically refer to the Revised Manuscript with Track change. Point 7. There are some issues with the formatting of the paper. Eq. (4), (5) (8); The title and body of Table 1 are separated. I suggest the author use the latex template of PLOS ONE. Response 7：We have modified the paper according to the formatting requirements of PLOS ONE and reorganized the equations. Specifically refer to the Revised Manuscript with Track change. Point 8. In table 1, the “point” in the table is redundant. Response 8："point" was redundant, and we have made the correction in the table 1. Point 9. Most of the comparison methods are too outdated. Response 9：Thank you for your suggestion. In order to compare newer methods, we have added newer methods in the Related Work section, and conducted an experimental comparison of the latest method, which is shown in Table 1. Response to Reviewer#2: Point 1. The percentage symbols in Equations 4, 5, 7, and 8 are misaligned. It is recommended to adjust the size of the percentage symbols to make them look more coordinated. Response 1：We revised the formula expression to make it clearer and more aesthetically pleasing. Specifically refer to the Revised Manuscript. Point 2. It is suggested that the author introduces more about the connection between different methods and their own work in the related work section. Explain how your method finds innovation among many methods, rather than merely listing the contents of others' work extensively. Response 2：Thank you for your suggestion. We have added content to enhance the relevance of the related work to this Manuscript, to highlight its relevance. Specifically refer to lines 127-133,171-174,181-183 of the Revised Manuscript with Track change. Point 3. It is recommended to provide more detailed explanations for the formulas in the text. Response 3：We have provided a more detailed explanation of the formulas in the Manuscript. Specifically refer to lines 289-330 of the Revised Manuscript with Track change. Point 4. The images inserted in the text are mostly of insufficient clarity; it is recommended to replace them with higher-resolution images. Response 4：Thank you for your suggestion. We have modified some unclear images and tried to make them more visually appealing, as shown in Fig 4. We have also removed Fig 1 due to copyright issues. Specifically refer to line 383 of the Revised Manuscript with Track change. Attachments Attachment Submitted filename: Response to Reviewers#2.docx https://doi.org/10.1371/journal.pone.0314086.r002
3 Oct 2024 Decision Letter - Ayesha Maqbool, Editor PONE-D-24-19727R1Learning features between neighboring points for point cloud classificationPLOS ONE Dear Dr. wang, 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. The article "Learning Features Between Neighboring Points for Point Cloud Classification" presents a valuable contribution; however, to enhance its quality, I recommend improving the analysis section and presenting the findings in greater depth. The objectives of the work should be further elaborated, with a clearer explanation of how these objectives are achieved. Providing a more structured presentation of the alignment between the research goals and results will significantly strengthen the paper. Please submit your revised manuscript by Nov 17 2024 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, Ayesha Maqbool, PhD Academic Editor PLOS ONE Journal Requirements: Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. [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: (No Response) Reviewer #2: (No Response) ******** 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: Partly Reviewer #2: Partly ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: N/A ****** 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: No ****** 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: No ****** 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: Most of comments have been addressed by the authors. However, all the figures in this paper look very rough, the images look very blurry. It is recommended to use vector graphics instead. Another concern is that most of the network figures look very similar to the figures in the publised papers, so the novely of this paper also need to be concerned. Reviewer #2: 1.There are several spelling and grammar errors in the text, such as the phrase "performed we this module" in the abstract. These details need to be meticulously proofread to prevent unnecessary mistakes that could impact the quality of the paper. 2.It has been noted that the images in the paper, particularly Figure 4, lack clarity. It is recommended to ensure that all images are of high resolution to facilitate easier viewing for readers. 3.In Table 1, the title and body are misaligned in several areas, which affects readability. Furthermore, the term "point" is redundant and should be eliminated from the table. 4.The explanations for formulas 4, 5, 7, and 8 lack sufficient detail. It is recommended to provide more comprehensive explanations of the derivation and underlying principles of these formulas. This will help ensure that readers can clearly grasp the derivation process and the physical significance of each step. 5.Although the "Related Work" section references relevant studies, the analysis primarily consists of a basic enumeration of their contents. It is advisable to emphasize the distinctions and innovations of your method in comparison to existing approaches to further strengthen the paper's persuasiveness. 6.Although the experimental results indicate that the method performs well on certain datasets, a more in-depth discussion is necessary regarding specific cases (e.g., the reasons why the method underperforms compared to DCNet on the FG3D dataset). Clarifying these differences will enhance readers' understanding of the method's strengths and weaknesses. 7.Some paragraphs transition rather abruptly, particularly between the introduction of the methods and the experiments section. Incorporating transitional sentences can enhance the overall flow and coherence of the paper's structure. ****** 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. Attachments Attachment Submitted filename: Reviewer Attachments for Manuscript.docx https://doi.org/10.1371/journal.pone.0314086.r003
Revision 2
1 Nov 2024 Author Response response to review #1: Thanks to your suggestions, we have replaced all the images with higher resolution images and Figure 4 has been redrawn with new tools to make it look better. You can view it below or in Revised Manuscript with Track change.For problems where the numbers are very close, because the classification task is close to saturation, even small overall accuracy gains still require quite complex improvements, and from the published networks, each percentage point of overall accuracy gain for the classification task requires approximately one to two years of experimentation by the relevant researchers around the world to improve the network performance. response to review #2:Detailed responses have been put into the “Response to Reviewer” file. Response 1：Thanks to your suggestion, we have carefully checked the whole text and corrected several grammatical and spelling errors. You can view in Revised Manuscript with Track change. Response 2：Thanks to your suggestions, we have replaced all the images with higher resolution images and Figure 4 has been redrawn with new tools to make it look better. You can view it in Revised Manuscript with Track change. Response 3：Thanks to your careful scrutiny, we've reworked the problems with the table 1. You can check it out in the Revised Manuscript. Response 4：Thanks for your suggestion, I have provided more explanations for formulas 4, 5, 7, and 8. You can check it out in the Revised Manuscript. Response 5：Thanks to your suggestion, we've added more differentiating descriptions to our related work to highlight the distinctiveness and innovation of our approach. You can check it out in the Revised Manuscript. Response 6：Thank you for your insightful suggestions. Indeed, networks targeted for fine-grained point cloud classification tasks differ in their design goals from those for traditional point cloud classification tasks. For the traditional point cloud dataset (ModelNet40), the network usually needs to learn the global structure of the point cloud samples in order to perform classification efficiently. However, since fine-grained point cloud datasets (FG3D) have relatively small interclass sample differences and relatively large intraclass sample differences, this property motivates the network to have to pay more attention to the local detailed features in order to achieve more accurate classification. fine-grained point cloud classification differs significantly from traditional point cloud classification in terms of the focus of feature learning. In order to focus on the ModelNet40 dataset, our proposed network concentrates on learning the global structure of the point cloud samples for the classification task, and thus has a lower accuracy than DCNet on the FG3D dataset. However, it is worth noting that our net exhibits superior performance on the fine-grained dataset FG3D compared to existing networks such as PCT. This is mainly due to the innovative design of the dual attention layer in terms of local feature capture, which enables the network to extract some fine features more efficiently, thus jointly improving the coarse- and fine-grained classification accuracy. We also analyse this problem in the manuscript，you can check it out in the Revised Manuscript. Response 7：The excesses of these two parts were indeed abrupt, we readjusted the transitional sentences to make the manuscript smoother. You can check it out in the Revised Manuscript. Attachments Attachment Submitted filename: Response to Reviewer.docx https://doi.org/10.1371/journal.pone.0314086.r004
5 Nov 2024 Decision Letter - Ayesha Maqbool, Editor Learning features between neighboring points for point cloud classification PONE-D-24-19727R2 Dear Dr. Wang, 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 will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, 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, Ayesha Maqbool, PhD Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0314086.r005
Formally Accepted
10 Dec 2024 Acceptance Letter - Ayesha Maqbool, Editor PONE-D-24-19727R2 PLOS ONE Dear Dr. Wang, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. 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. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Ayesha Maqbool Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0314086.r006

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