Next Article in Journal
Learning from Multiple Instances: A Two-Stage Unsupervised Image Denoising Framework Based on Deep Image Prior
Previous Article in Journal
Review of Machine-Learning Techniques Applied to Structural Health Monitoring Systems for Building and Bridge Structures
 
 
Review
Peer-Review Record

A Review of the Optimal Design of Neural Networks Based on FPGA

Appl. Sci. 2022, 12(21), 10771; https://doi.org/10.3390/app122110771
by Chenghao Wang 1 and Zhongqiang Luo 1,2,*
Reviewer 1: Anonymous
Reviewer 2:
Appl. Sci. 2022, 12(21), 10771; https://doi.org/10.3390/app122110771
Submission received: 24 September 2022 / Revised: 17 October 2022 / Accepted: 20 October 2022 / Published: 24 October 2022

Round 1

Reviewer 1 Report

The manuscript is well written and well structured. The authors have presented in detail the state-of-the-art techniques for optimal design of neural networks based on FPGA. Some minor changes that can be incorporated are as follows:

Fig. 2, Fig. 4 and Fig. 5 can be replaced with better versions.

The blocks in Fig. 6 should include references in addition to the texts.

 

Overall a good manuscript with rich reference.

Author Response

Please see the attachment.

Author Response File: Author Response.doc

Reviewer 2 Report

This article is organized and written well. Please read and check on the typos in the text, for example, it is "Generative Adversarial Networks (GAN)" not "Generative networks Adversarial Networks (GAN)" on Page 5, Lines 175 and 176. 

Any abbreviations must be defined first before using.

Appropriate citations need to be added to the caption of each figure if it is adopted or modified from the published articles such as Figs. 3, 7, 8, 9, 13, 15 ~ 20. 

Author Response

Please see the attachment.

Author Response File: Author Response.doc

Back to TopTop