Research on Fruit Spatial Coordinate Positioning by Combining Improved YOLOv8s and Adaptive Multi-Resolution Model
Round 1
Reviewer 1 Report
review attached as a PDF
Comments for author File: 
Comments.pdf
There
were many grammatical and spelling errors throughout the document. Please address those in the revised manuscript.
Author Response
Please refer to the attached document.
Author Response File: Author Response.pdf
Reviewer 2 Report
This study states that it can significantly improve the efficiency of automatic fruit picking equipment. In particular, the accuracy of fruit detection and localization is extremely important in this regard. But current methods rely on expensive tools such as depth cameras and LiDAR. This study proposes a low-cost method based on monocular images to obtain target detection and depth estimation. The details and results of the study are very important from an academic point of view. But again, there are some points in the study that are not understood and need to be corrected.
1- The literature part should be developed a little more. There are many studies in the literature on this subject and there should be criteria such as the results of these studies, the method used and the success performances. Literature reviews should cover at most the last three years.
for example: https://www.mdpi.com/2073-4395/13/2/451
https://www.mdpi.com/2073-4395/13/6/1618
2- 53.line CNN, 106.line EIoU, 108. it is necessary to write the exact forms of abbreviations such as line RGB-D. Please write down the explicit versions of the abbreviation terms that have not been fully rendered in this way throughout the study.
3- Why was YoLoV8 preferred in the study? Was this model chosen by making a comparison with other versions of the YoLo model?
4- 5. it would be appropriate to change the section to "conclusion and discussion". In this section, some more suggestions may be offered for future studies.
5- 2.3. have the results been obtained by conducting a study with the model on the datasets given in the title? If the study has been done, can the success of the model be shared for each dataset?
6- Can a maximum of 150 cm be enough for the model when selecting the distance in the images? For example, if a mobile system is used to estimate the number of fruits on any tree, how accurate can this model be in a software that integrates this model from 3 or 4 meters?
Author Response
Please refer to the attached document.
Author Response File: Author Response.pdf
