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Article
Peer-Review Record

Fully Automated Pose Estimation of Historical Images in the Context of 4D Geographic Information Systems Utilizing Machine Learning Methods

ISPRS Int. J. Geo-Inf. 2021, 10(11), 748; https://doi.org/10.3390/ijgi10110748
by Ferdinand Maiwald 1,2,*,†,‡, Christoph Lehmann 3,‡ and Taras Lazariv 3
Reviewer 1:
Reviewer 2: Anonymous
Reviewer 3: Anonymous
ISPRS Int. J. Geo-Inf. 2021, 10(11), 748; https://doi.org/10.3390/ijgi10110748
Submission received: 22 September 2021 / Revised: 28 October 2021 / Accepted: 1 November 2021 / Published: 4 November 2021

Round 1

Reviewer 1 Report

The paper is very good, the subject is very interesting and the applied methodology is original and well described. The final results are clear.
Nothing else to say.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Dear Authors, 

I have reviewed the paper entitled "Fully Automated Pose Estimation of Historical Images in the Context of 4D Geographic Information Systems Utilizing Machine Learning Methods".  I read the article several times and I have to admit that it is a very interesting and well written manuscript. 

 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Dear authors, I think the article is very interesting.

It would be appropriate to add the time-consuming to the tested methods for comparison.

Would it also be possible to add some numbers to the table with green lines (in apendix)?
 
Surely readers would appreciate information on whether you expect to implement these algorithms in a some commercial version of the software. 

Thanks

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.


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