Review Reports

Round 1

Reviewer 1 Report

The paper proposes a lightweight first-stage object detection network, AAL-Net, used for road surface defects. A lightweight feature extraction module (LF) and NAM attention module are used to ensure the accuracy and real-time of the pothole detection process. A data augmentation method is also employed to further improve the detection accuracy and robustness of the AAL-Net. The results indicate that this network has better performance than other existing networks. Overall, this paper is well organized, and relevant methods are comprehensively described. Some of my comments and suggestions are given below.

 

(1) The authors should pay more attention to the grammar check. For example, ‘parameter’ and ‘are’ (see lines 275 and 277) are inconsistent. In line 299, ‘performe’ should be replace by ‘performed’.

 

(2) Section 2.1 introduces some lightweight neural networks, such as ShuffleNet and MobileNet. The application of lightweight networks for defect detection in engineering areas should be introduced as well. Here are some examples: doi:10.3390/electronics8111354; doi: 10.1007/s00170-022-10335-8.

 

(3) Section 4.2.1 introduces the relevant experimental settings, such as batch size, learning rate, and optimizer. The authors should clarify why these parameters are used and whether different parameters have been tested and compared.

 

(4) In Figures 8, 9, 10, 12, the scales of y-axis should be added.

 

(5) The results of Section 4 indicate that AAL-Net is superior to other existing networks. It is recommended that the authors should conduct in-depth comparison and analysis to explain why AAL-Net has the best performance, or clarify the advantages of the proposed model over the existing ones. Otherwise, only descripting comparison results is not good enough. More discussion and analysis should be added.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Complete comments and suggestions are provided in the file attached.

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Overall, the authors have managed to respond to the reviewer’s comments. This manuscript with high quality can be accepted for publication.