PONE-D-23-31505How deep is your art: an experimental study on the limits of artistic understanding in a single-task, single-modality neural networkPLOS ONE

Dear Dr. Agha Zahedi,

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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: No

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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 research article presents a thought-provoking investigation into the capabilities of Deep Convolutional Neural Networks (DCNN) in interpreting modern conceptual artwork. The study addresses the intricate nature of art interpretation, which is known for its multidimensional and subjective characteristics.

One of the key strengths of this paper is the clear articulation of two hypotheses regarding the classification of artwork properties by the DCNN model. The hypotheses suggest that the model utilizes Exhibited Properties, such as shape and color, for classification, while ignoring Non-Exhibited Properties like historical context and artist intention. Through a meticulously designed methodology, the experimental results supported these hypotheses, highlighting the DCNN's focus on exhibited properties for artwork classification.

However, the innovations in this paper focus on transitional convolution neural network, and the methods and theoretical innovations are not sufficient. The author must dig deeper into the innovation points before the article can be accepted by PONE.

Secondary, this paper offers valuable insights into the intersection of art and artificial intelligence, raising important questions about the boundaries of artistic understanding in neural networks. This paper should do more research in the area of intricate relationship between technology and creativity, for the sake of better explanation about the significance and necessity of your research

Thirdly, authors should present some picture about the art in your paper in order to better understand.

Finally, authors should share their code and project for easier reproducibility and persuasion.

Reviewer #2: The manuscript "How Deep is Your Art: An Experimental Study on the Limits of Artistic Understanding in a Single-Task, Single-Modality Neural Network" investigates the shortcomings in the Deep Convolutional Neural Network (DCNN) models by experimenting the degree to which a DCNN model can correctly distinguish modern conceptual artwork into the galleries taking into account Exhibited Properties for classification (shape and color) but not Non-Exhibited Properties (historical context and artist intention).

Based on previous comments, the manuscript has improved significantly; however, some typos and wrong sentence structure can be improved. Also, some improvement is needed in presenting the number of images in each of the datasets/galleries clearly and scaling them to fit the journal template guidelines. My other concern is whether the manuscript exceeds the page limits. Overall, the manuscript can be more structured and aligned to make the paper easy to follow.

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Reviewer #1: No

Reviewer #2: No

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How deep is your art: an experimental study on the limits of artistic understanding in a single-task, single-modality neural network

PONE-D-23-31505R1

Dear Dr. Agha Zahedi,

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,

Dang N. H. Thanh, Ph.D

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

As recommendation from the reviewers and after checking the revision, I recommend acceptance of the paper.

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

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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

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

Reviewer #1: Yes

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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

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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

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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 authors have answered and revised all my concerned question, so I have no more questions anymore in this step.

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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

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