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Sensors
Volume 23
Issue 8
10.3390/s23083977
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Article
Peer-Review Record

Inspection of Enamel Removal Using Infrared Thermal Imaging and Machine Learning Techniques

Sensors 2023, 23(8), 3977; https://doi.org/10.3390/s23083977
by Divya Tiwari 1,*, David Miller 1, Michael Farnsworth 1, Alexis Lambourne 2, Geraint W. Jewell 3 and Ashutosh Tiwari 1
Reviewer 1:
Milan Durdán
Reviewer 3:
Mahdi Yeganeh
Reviewer 4: Anonymous
Sensors 2023, 23(8), 3977; https://doi.org/10.3390/s23083977
Submission received: 27 February 2023 / Revised: 20 March 2023 / Accepted: 7 April 2023 / Published: 14 April 2023
(This article belongs to the Special Issue Sensing for In-Process Monitoring of High-Value Manufacturing Processes)

Round 1

Reviewer 1 Report

I have some remarks for the authors:

- It is necessary to explain abbreviations in the text, such as ML, ANN, and CNN.

- The introductory description of sections 2 and 3 is missing.

- The reference to the figure should not be in the form of in "Figure 1“ but in "Fig. 1"., similarly for other images. The phrase Figure is used at the beginning of a sentence.

- Figure 3, wire 3 had a darker color all the time. What caused it?

-  In the text “of 5th, 6th, and 7th“, th should be a superscript everywhere.

- The reference to Figure 6 is missing in the text. 

-   Figure 7 is divided into two pages.

 

 

Author Response

Please see attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Your manuscript is well designed and all the parts are well discussed. 

Author Response

We thank the reviewer for their feedback. There are no comments to address.

Reviewer 3 Report

Please address all comments in the attached file. Modify the abstract and introduction according the comments and provide more new papers.

Comments for author File: Comments.pdf

Author Response

Please see the attachment and Appendix A.

Author Response File: Author Response.pdf

Reviewer 4 Report

This paper developed a metho for inspection of enamel removal using infrared thermal imaging and machine learning techniques. The topic is interesting and valuable. The results showed that the best model for enamel classification accuracy was the Gaussian Mixture Model with Expectation Maximisation. Overall, the paper is well written. I have some minor comments here.

1. the test proposed in this paper is simple. Did you consider the influence of distance, angle and enviroment temperature? 

2. Can the proposed method work under moving situation? (the object is moving)

3. The training set should  contain the samples collected at different situations.

4. Did you consider using neural network to classify the results?

 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

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