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Article
Peer-Review Record

Machine Learning and Image-Processing-Based Method for the Detection of Archaeological Structures in Areas with Large Amounts of Vegetation Using Satellite Images

Appl. Sci. 2023, 13(11), 6663; https://doi.org/10.3390/app13116663
by José Alberto Fuentes-Carbajal *, Jesús Ariel Carrasco-Ochoa, José Francisco Martínez-Trinidad and Jorge Arturo Flores-López
Reviewer 1: Anonymous
Reviewer 2:
Appl. Sci. 2023, 13(11), 6663; https://doi.org/10.3390/app13116663
Submission received: 21 March 2023 / Revised: 13 May 2023 / Accepted: 15 May 2023 / Published: 30 May 2023

Round 1

Reviewer 1 Report

The paper proposed a machine learning and image processing based-method for the detection of archaeological structures. The research of this paper is interesting. However, the paper has following concerns.

1. The Introduction is too simple, which needs to improve further.

2. The motivation of the proposed method is not clear.

3. The main contributions of the paper should be concluded in Introduction.

4. The resolution of Figures is low.

5. Why do the authors choose Canny, Laplacian, and Sobel as filters in this paper, please give detailed introduction.

6. The manually labeled samples in Fig. 3 belong to a continuous regions. The readers may concerns the case that labeled samples are scattered. So, the experiments under this situation should be considered.

7. The authors are suggested to give an algoithm to show the process of the proposed method.

8. The information of reference 29 is incomplete.

Author Response

We attach PDF with the answers.

Author Response File: Author Response.pdf

Reviewer 2 Report


Comments for author File: Comments.pdf

Author Response

We attach PDF with the answers.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Many thanks to the authors for improving their manuscript. The authors have addressed my concerns and it seems the paper is ready for publication.

Reviewer 2 Report

All comments were addressed. I think the paper is ready for publication. 

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