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Article
Peer-Review Record

Comparison of Cognitive Differences of Artworks between Artist and Artistic Style Transfer

Appl. Sci. 2022, 12(11), 5525; https://doi.org/10.3390/app12115525
by Yikang Sun 1, Yanru Lyu 2, Po-Hsien Lin 3 and Rungtai Lin 3,*
Reviewer 1: Anonymous
Reviewer 2:
Appl. Sci. 2022, 12(11), 5525; https://doi.org/10.3390/app12115525
Submission received: 3 May 2022 / Revised: 22 May 2022 / Accepted: 27 May 2022 / Published: 29 May 2022
(This article belongs to the Special Issue User Experience for Advanced Human-Computer Interaction II)

Round 1

Reviewer 1 Report

The manuscript entitled 'Comparison of Cognitive Differences of Artworks between Artist and Artistic Style Transfer' has clear objectives, is well written and sets out a series of findings for the field.
In the methodology, the authors do not explain what the neural network consisted of (the different AI algorhitms) that converted the 6 original images? Nor what criteria did the artists use or what indications did they give them to solve the imitation? These decisions/approaches could be used as categories of analysis in relation to the survey results. One of the easily detectable appearances of the computer IA result is the low level of suspension of disbelief due to the graphic visual disconnection between generated zones.
Likewise, this section does not specify which creativity variables were used to measure 'the creative mode of the stimulus'? Later, in the results section, we see that it refers to the line, color, light and shade, stroke and detail. None of these variables appear as items in the graphic creative. In fact, I think the term used should be removed and search for the specific word.
Nor is it defined how the questionnaires were supplied? What is the population?
Please review these issues.

Author Response

Comment: The manuscript entitled ‘Comparison of Cognitive Differences of Artworks between Artist and Artistic Style Transfer’ has clear objectives, is well written and sets out a series of findings for the field.

Response: Thank you very much for your affirmation of our research! We know that this does not mean that our research is perfect. In fact, the questions you’ve asked and the suggestions you’ve given us have been a great inspiration to make this article even more complete. Next, we will respond to your comments one by one.

 

Comment: In the methodology, the authors do not explain what the neural network consisted of (the different AI algorithms) that converted the 6 original images? Nor what criteria did the artists use or what indications did they give them to solve the imitation? These decisions/approaches could be used as categories of analysis in relation to the survey results. One of the easily detectable appearances of the computer AI result is the low level of suspension of disbelief due to the graphic visual disconnection between generated zones.

Response: Thank you so much for your comments! We complement the algorithms used and describe in detail the processes by which these stimuli are produced. Since we didn’t want to put any pressure on the 2 self-taught artists or influence their creations, we only asked them to create according to their own understanding. We think this is also good for the viewer, because we ask them to make judgments based on intuition. On the last point, when we number stimuli, we take a random approach, and we intend to combine computer-created paintings with human-created paintings. Consistent with the motivations described above, we want to minimize possible obstacles that affect audience judgment.

 

Comment: Likewise, this section does not specify which creativity variables were used to measure ‘the creative mode of the stimulus’? Later, in the results section, we see that it refers to the line, color, light and shade, stroke and detail. None of these variables appear as items in the graphic creative. In fact, I think the term used should be removed and search for the specific word.

Response: Thank you for your advice! Although art appreciation is highly subjective, we still hope to use some keywords as a criterion for evaluation. We discussed with art and aesthetic experts and synthesized everyone’s suggestions to evaluate the five attributes of line, color, light and shadow, brushstrokes, and details. We’ve also added a sixth option: Only “intuition”, hoping to get more authentic feedback from viewers. For all of the above reasons, we hope you will understand and understand our choice to retain these words. However, since this article is part of a project, during the follow-up research process, we will further check the relevance of these words based on your comments and combined with the feedback of this respondent, or replace them with other words under the premise of satisfying the purpose of the research.

 

Comment: Nor is it defined how the questionnaires were supplied? What is the population?

Response: Thank you again for reviewing it so meticulously! Due to the impact of the COVID-19 and other factors, the questionnaire of this study was produced and delivered in the form of Google Form. The questionnaire was officially launched on April 12, 2021, and we waited 19 days in the hope that more people would participate. In the end, a total of 750 valid questionnaires were received. What’s more, the data that support the findings of this study are openly available in the repository Open Science Framework at http://doi.org/10.17605/OSF.IO/PDT6Y

Reviewer 2 Report

dear authors:

my comments are as follows

1- the introduction is not clear, rewrite it more clearly.

2- in Materials and Methods: you need more clarify the technique you used in detail.

3- in Materials and Methods: add a figure to clarify your system and the steps of the methodology.

Author Response

Comment: the introduction is not clear, rewrite it more clearly.

Response: Thank you very much for your comments! We have revised and reformulated the content of the first part to ensure that it clearly presents the background, status and purpose of the study.

 

Comment: in Materials and Methods: you need more clarify the technique you used in detail.

Response: Thank you for your very detailed review! We theorize about your intentions: Although this article does not cover technical issues, it is necessary to explain to the reader what technologies we have adopted. The process by which stimulants are produced, and the algorithms we used have been supplemented in “2.1. Stimuli”.

 

Comment: in Materials and Methods: add a figure to clarify your system and the steps of the methodology.

Response: Thank you again for your advice! We’ve added a figure to this section.

 
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