All reviews of published articles are made public. This includes manuscript files, peer review comments, author rebuttals and revised materials. Note: This was optional for articles submitted before 13 February 2023.
Peer reviewers are encouraged (but not required) to provide their names to the authors when submitting their peer review. If they agree to provide their name, then their personal profile page will reflect a public acknowledgment that they performed a review (even if the article is rejected). If the article is accepted, then reviewers who provided their name will be associated with the article itself.
The authors have revised the article considerably and reviewers agree on acceptance.
[# PeerJ Staff Note - this decision was reviewed and approved by Xiangjie Kong, a PeerJ Section Editor covering this Section #]
All issues are addressed.
All issues are addressed.
All issues are addressed.
Issues have been resolved already.
no comment
no comment
no comment
The authors should revise the article to improve technical writing, explaination of equations, and research contributions.
**PeerJ Staff Note:** Please ensure that all review and editorial comments are addressed in a response letter and that any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate.
**Language Note:** The review process has identified that the English language must be improved. PeerJ can provide language editing services - please contact us at copyediting@peerj.com for pricing (be sure to provide your manuscript number and title). Alternatively, you should make your own arrangements to improve the language quality and provide details in your response letter. – PeerJ Staff
1. Issues in the abstract: The abstract has several weaknesses, including a lack of clarity and precision in its language, insufficient details on specific challenges in small object detection, and a failure to provide concise explanations for key components of the proposed algorithm, such as the Multi-branch Attention Module (MBAM) and the SimAM attention mechanism. Additionally, the abstract lacks a comparative analysis of how MBAN addresses identified challenges compared to existing methods, and it doesn't offer sufficient information on the experimental methodology or validation metrics used.
2. The motivation for this research is missing. Authors should add a few lines about the motivation just before the contributions.
3. I suggest that the authors proofread the entire paper and improve its quality of writing.
1. The discussion of the mathematical equations is very limited.
2. The author does not declare the structure of their proposed algorithm. I suggest that the authors provide an algorithmic representation of the proposed algorithm.
3. Authors are required to add the utilized hyperparameters, in the form of a table, for the implementation of the method.
The discussion of the results especially of the table 3 - 6 is very limited.
Authors are required to justify achieving such high performance as depicted in these tables.
The conclusion section can be improved by emphasizing the most important findings (numerical results), highlighting the limitations of the research, and making recommendations for future research.
1. The authors have presented a novel multi-branch attention module that consists of two designs; a multi-branch structure and the SimAM parameter-free attention mechanism.
2. The concept presented in this work is interesting, however, the authors can combine Contributions 1 & 2 to make a single contribution in the Introduction section.
3. The literature should discuss multi-branch attention methods used previously.
Which YOLO network is selected for the integration of novel MBAN module?
no comment
Line 10 --> has
Line 13 --> object
Line 21 --> demonstrates
Line 36 --> uses
Line 57 --> an MBAN
Line 75 --> outlined
Line 149 --> a strengthened
Line 189 --> an object/objects
Line 204 --> makes
Line 389 --> Remove one “be”
All text and materials provided via this peer-review history page are made available under a Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.