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Authors have addressed all the comments and it is ready for publication for this journal.
[# PeerJ Staff Note - Please address the final comments from R2 while in production #]
[# PeerJ Staff Note - this decision was reviewed and approved by Jyotismita Chaki, a 'PeerJ Computer Science' Section Editor covering this Section #]
This revision is satisfactory.
Experiments are valid
All appropriate.
Good
Modified according to the inputs given
Modified according to the inputs given. Check the general comments
Author says "Regarding the run time of the methods, classic Faster R-CNN detects 0.603 sn,
while fine-tuned Faster R-CNN detects 0.633 sn. Classic MobileNet detects 0.046 sn, while fine-tuned
MobileNet detects 0.048 sn. Classic YOLO V4 and fine-tuned YOLO V4 detect 0.235 and 0.240 sn,
respectively". Check the unit of measurement. This is from abstract but in results and discussion author says "On the 507 other hand, regarding the run time of the proposed fine-tuned based methods, fine-tuned Faster R-CNN, 508 MobileNet, YOLO V4, YOLO V5, and YOLO V7 detect objects about 0.633, 0.048, 0.240, 0.015 and 509 0.009 seconds, respectively."
Authors should carefully review all the comments from the reviewers in particular to focus on the experimental design, and results and discussion sections. Also, it is strongly recommended authors ask a proficient English speaker to proofread the paper before the next submission.
[# PeerJ Staff Note: Please ensure that all review comments are addressed in a rebuttal letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate. It is a common mistake to address reviewer questions in the rebuttal letter but not in the revised manuscript. If a reviewer raised a question then your readers will probably have the same question so you should ensure that the manuscript can stand alone without the rebuttal letter. Directions on how to prepare a rebuttal letter can be found at: https://peerj.com/benefits/academic-rebuttal-letters/ #]
What do you mean by "natural image" here?
English language of the article should be improved - for ex, in the abstract "Faster R-CNN model achieves an average F1 score of 0.762 and the YOLO V4 model an average of 0.879 F1 scores showed that the model obtained an average of 0.945" - which one obtained 0.945 here?. Even it is understandable, not a correct way to express the contents. So check the article for grammatical and sentence fragment errors like this.
In the introduction - "c images taken with 360° Vandeviver" - Vandeviver is a camera or person?
in the introduction - "Variability of light, background clutter, severe blur, inconsistent resolution, etc." what is this? no meaningful sentence.
In the related work section - line number 80, 82, 85, 87, etc. are having reference the author's name two times. Check the article for this kind of error.
Clear language revision is needed.
Technical details like the layer structure of Faster R-CNN and YOLO5 should be included.
Provide the intermediate output of the models for the given figure 1.
sample data have been provided; they are robust.
As per the given data validity of the findings matches.
Figure 3 caption is appropriate.
Rename table 1 caption as "Dataset Summary"
What are the class properties of the labels
1. INTRODUCTION part has lag of clarity. It need to be strengthened.
2. Similarly the related work section also need to be improved. There is no much work had been referred.
3. Author says “For this reason, the YOLO model, which is widely used 244 in real-time object detection and achieved successful results in small object detection, has been used as a 245 CNN-based deep learning method in order to increase the prediction performance of the designed system 246 and reduce the computational cost. The results obtained are presented in Chapter .” It is a too lengthy sentence and it has lot of mistakes.
4. Result and discussion part is not up to the level of research. Detailed discussion is needed.
5. Novelty projection in the manuscript is lagging.
6. The overall ambition of the manuscript is low in terms of content.
7. Table 2. All Metrics of CNN Models has lot of unwanted data. It can be minimized.
8. Latest references are needed.
9. What the Figure 3. Locations of Images communicates? Is it required?
The projection of experimental design is very low.
no comment
Language needs to be improved.
The manuscript is a well-written and cited related paper in an appropriate manner. The authors well described the data set and empirical evaluation part too.
Designing and evaluation are well-written.
It is properly mentioned in the paper. The contributions help the research community.
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