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Article
Peer-Review Record

MediaPipe’s Landmarks with RNN for Dynamic Sign Language Recognition

Electronics 2022, 11(19), 3228; https://doi.org/10.3390/electronics11193228
by Gerges H. Samaan 1, Abanoub R. Wadie 1, Abanoub K. Attia 1, Abanoub M. Asaad 1, Andrew E. Kamel 1, Salwa O. Slim 1, Mohamed S. Abdallah 2,3,* and Young-Im Cho 2,*
Reviewer 1: Anonymous
Reviewer 2:
Electronics 2022, 11(19), 3228; https://doi.org/10.3390/electronics11193228
Submission received: 3 August 2022 / Revised: 19 September 2022 / Accepted: 1 October 2022 / Published: 8 October 2022
(This article belongs to the Special Issue AI and Smart City Technologies)

Round 1

Reviewer 1 Report

The key contribution of this work should be conveniently explained.

MediaPipe is presented as the grounding work but it should not be supported on a non-published preprint.

RNN and DSL acronyms should be presented.

The sentence in line 9 is not correct: "DSL10-Dataset was created in response to the scarcity of English video-based datasets."

Models in line 61 require references.

The first sentence in line 72 should be fixed.

The dataset in line 140 should be fixed.

Figures 1 a b and c. are in low resolution and stretched.

Figure 2 is stretched and requires a reference to the original work. Please, check the other ones.

Figure 3 requires a reference.

The sentence in line 169 "The MediaPipe framework provides a solution for most of the DSL problems."  

DSL10-Dataset requires a reference.

The link at line 273 should be replaced by a reference.

The size of the font in the Tables is too huge.

Figure 8 includes stretched images.

Computations on lines 163 and 165 should be replaced by formulas.

This statement requires further discussion "This experiment shows the pros and cons of including face keypoints.".

The dataset is not correctly described and does not include labels.

 

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 2 Report

Dear Author,

I have some comments on your article:

1. In section: 3.1. Input Data - please write more about the input data and how to obtain them

2. Please improve the quality of figure 1 to figure 3

3. Literature should be checked if there are no newer items. Especially from the last 18 months. It would be good to add several references.

4. Please correct the text formatting in the tables

5. Experimental Results - Please describe the results in more detail

6. In the summary of the article, please provide more technical information about the practical possibility of implementing the proposed method.

Best regards

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The paper has been improved with the and all previous comments have been addressed.

 

Reviewer 2 Report

Dear Authors,

Thank you very much for introducing changes that have improved the quality of the article. I have no more comments.

Best regards

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