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Article
Peer-Review Record

Research on a Dynamic Algorithm for Cow Weighing Based on an SVM and Empirical Wavelet Transform

Sensors 2020, 20(18), 5363; https://doi.org/10.3390/s20185363
by Ningning Feng 1,2, Xi Kang 1,2, Haoyuan Han 3, Gang Liu 1,2, Yan’e Zhang 2,* and Shuli Mei 3
Reviewer 1:
Reviewer 2: Anonymous
Sensors 2020, 20(18), 5363; https://doi.org/10.3390/s20185363
Submission received: 14 August 2020 / Revised: 11 September 2020 / Accepted: 16 September 2020 / Published: 18 September 2020
(This article belongs to the Special Issue Sensing Technologies for Agricultural Automation and Robotics)

Round 1

Reviewer 1 Report

This paper proposes a dynamic algorithm for cow weighing based on SVM and empirical wavelet transform. This topic is practical and interesting. The reviewer’s comments are given below.

  1. The author should introduce that how to estimate the true weight of a cow by using the dynamic weighing data.
  2. How to distinguish between the slow and fast signal should be further clarified.
  3. It seems that the proposed algorithm does not need the data about the walking speed. Can the speed measuring device be replaced by an algorithm?
  4. The improvement of the proposed algorithm is not significant comparing with the existing EMD algorithm. Maybe speed is not the main factor causing measurement errors.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

The summary and conclusions should briefly outline the approach.

It seems strange in the graphs to present the units of measurement by a fraction.

The experimental equipment should be described in more detail: parameters, accuracy.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The author has addressed all the question of the reviewer,and the reviewer has no other questions.

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