Next Article in Journal
Application of Segmentation and Fuzzy Classification Techniques (TSK) in Analyzing the Composition of Lightweight Concretes Containing Ethylene Vinyl Acetate and Natural Fibers Using Micro-Computed Tomography Images
Previous Article in Journal
Design and Implementation of a Model Predictive Formation Tracking Control System for Underwater Multiple Small Spherical Robots
 
 
Article
Peer-Review Record

Research on Algorithm for Authenticating the Authenticity of Calligraphy Works Based on Improved EfficientNet Network

Appl. Sci. 2024, 14(1), 295; https://doi.org/10.3390/app14010295
by Weijun Wang, Xuyao Jiang, Hai Yuan *, Jinyuan Chen, Xintong Wang and Zucheng Huang *
Reviewer 1: Anonymous
Reviewer 2:
Appl. Sci. 2024, 14(1), 295; https://doi.org/10.3390/app14010295
Submission received: 29 November 2023 / Revised: 20 December 2023 / Accepted: 26 December 2023 / Published: 28 December 2023

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper presents research on automatic recognition of forgery in calligraphy works.

I have a few concerns regarding the paper.  

The research presented in the paper can be divided into two steps. In the first step bounding boxes of characters are detected and in the second step deep learning is used.  

Regarding the first step I have a major concern such that authors did not compare their method of creating bounding boxes to other existing method. The topic is not new therefore a lot of other method were proposed.  

Apart from that it is not clear for me how data augmentation (Sect. 2.3.) was applied to images. Was is performed manually or with the use of some automation? 

In Sect. 2.2.1 and 2.2.2. Authors should provide references to papers presenting equations included in these sections.  

Regarding the second step in which neural network were used it is not clear how the network proposed by authors of the paper differs from existing networks.  

Moreover information about the number of images used for testing with regard to number of test images is not presented in the paper.  

Authors should also provide references to papers describing different algorithm which they included in tables 1, 2 and 3.

Author Response

Dear reviewer, thank you for your careful review, we have made a point-to-point reply to your suggestions, please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

1.Describe how data addition happens in your algorithm?

2.If the symbols are handwritten, then there may be deviations in the angle of inclination of the main strokes, the thickness of the strokes - how is this taken into account?

3.Your literature is mostly three years old. I think it should be eliminated, because there is a lot of development in the field of artificial intelligence

4. Calligraphic fonts are very different. They are distinguished by new forms and drawings. In this study, it is not clear how this or that letter is identified.

Author Response

Dear reviewer, thank you for your careful review, we have made a point-to-point reply to your suggestions, please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I have no further comments to the paper.

Reviewer 2 Report

Comments and Suggestions for Authors

no comments

Back to TopTop