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Article
Peer-Review Record

Recognizing Similar Musical Instruments with YOLO Models

Big Data Cogn. Comput. 2023, 7(2), 94; https://doi.org/10.3390/bdcc7020094
by Christine Dewi 1, Abbott Po Shun Chen 2,* and Henoch Juli Christanto 3,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Big Data Cogn. Comput. 2023, 7(2), 94; https://doi.org/10.3390/bdcc7020094
Submission received: 11 April 2023 / Revised: 5 May 2023 / Accepted: 8 May 2023 / Published: 10 May 2023
(This article belongs to the Special Issue Computational Collective Intelligence with Big Data–AI Society)

Round 1

Reviewer 1 Report

Comments for "Yolov7 for Identifying Similar Musical Instruments based on  Deep Learning"

1. The Yolov7 is a kind of deep learning framework, so the title is redundant.

2. The importance of recognizing musical Instruments is unclear in the introduction

3. Figure 7 only provide AUPRC, the AUROC should be included also.

4. There are two table 4 in the paper

5, Table 3 and first table  4 should be summarized together

6. quality for FIgure 8 should be improved

7. Authors only consider the Yolo V5 and Yolo V7 in their paper rather than other frameworks, they should provide the resaon

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 2 Report

·       The research issue and objectives can be highlighted in a separate paragraph in the introduction.

·       In section 2.1, the citations such as M. Ju et al., [15] and others are wrong; you don’t cite with initials, so the citations should be as follows: Ju et al. [15] etc. The authors should correct all the in-text citations.

·       I can see the authors only split their dataset into two ratios: testing and training. I believe these datasets are used during the training process. Did the authors test the model? If yes, what dataset did they use? I expect them to use a dataset that has not undergone the training process.

·       I can’t see the model histories; this should be included

·       The dataset size, collection process, and range are not mentioned. The authors should also mention the ratio of the data split as well.

·       The authors should state how the study performance was accessed or evaluated.

·       How did the authors tune the optimal hyperparameter of all models? It should be described clearly.

·       Overall, the English language and presentation style should be improved significantly. There contained a lot of grammatical errors and typos. I suggest you have a colleague proficient in English and familiar with the subject matter review your manuscript or contact a professional editing service.

 

 

 

 

the English language and presentation style should be improved significantly. There contained a lot of grammatical errors and typos. I suggest you have a colleague proficient in English and familiar with the subject matter review your manuscript or contact a professional editing service.

 

 

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

authors have fixed all my early concerns

Reviewer 2 Report

All my comments have been attended to

 

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