Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Weighted Mean00:57

Weighted Mean

5.9K
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
5.9K
Multiple Regression01:25

Multiple Regression

3.4K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.4K
Apparent Weight01:09

Apparent Weight

9.2K
True weight is the measure of the gravitational force acting on an object. However, if the object accelerates, its measured weight is different from its true weight. Similar observations can be made when the object is submerged in water. An object's weight in water is its apparent weight, which is equal to the difference between its true weight and the buoyant forces.
Consider a person standing on a bathroom scale inside an elevator. If the scale is accurate at rest, its reading equals the...
9.2K
End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

801
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
801
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

222
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
222
Regression Toward the Mean01:52

Regression Toward the Mean

6.6K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

In situ secondary structure imaging of protein phase separation and aggregation by hyperspectral stimulated Raman scattering microscopy.

Nature communications·2025
Same author

Estimation of Sow Backfat Thickness Based on Machine Vision.

Animals : an open access journal from MDPI·2024
Same author

Predicting egg production rate and egg weight of broiler breeders based on machine learning and Shapley additive explanations.

Poultry science·2024
Same author

Circadian regulation of translation.

RNA biology·2024
Same author

Efficient Aggressive Behavior Recognition of Pigs Based on Temporal Shift Module.

Animals : an open access journal from MDPI·2023
Same author

Circadian clocks are modulated by compartmentalized oscillating translation.

Cell·2023

Related Experiment Video

Updated: Nov 3, 2025

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.8K

Pig Weight and Body Size Estimation Using a Multiple Output Regression Convolutional Neural Network: A Fast and Fully

Jianlong Zhang1,2, Yanrong Zhuang1,2, Hengyi Ji1,2

  • 1College of Water Resources & Civil Engineering, China Agricultural University, Beijing 100083, China.

Sensors (Basel, Switzerland)
|June 2, 2021
PubMed
Summary

This study developed a modified Xception convolutional neural network (CNN) to automatically estimate pig weight and body size. The model accurately predicts key measurements, aiding in efficient farm management.

Keywords:
body sizeconvolutional neural networkdeep learningestimationpig weight

More Related Videos

Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.5K
Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction
06:19

Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction

Published on: August 16, 2024

636

Related Experiment Videos

Last Updated: Nov 3, 2025

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.8K
Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.5K
Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction
06:19

Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction

Published on: August 16, 2024

636

Area of Science:

  • Agricultural technology
  • Computer vision
  • Machine learning

Background:

  • Accurate pig weight and body size are crucial for producers.
  • Increasing farm scale makes manual measurement difficult and time-consuming.

Purpose of the Study:

  • To develop an automated system for estimating pig weight and body size.
  • To evaluate the performance of multiple convolutional neural network (CNN) architectures for this task.

Main Methods:

  • Modified DenseNet201, ResNet152 V2, Xception, and MobileNet V2 into multiple output regression CNNs.
  • Trained and tested models on pig measurement data.
  • Selected the modified Xception model as the optimal solution.

Main Results:

  • The modified Xception model achieved high accuracy in estimating body weight (BW), shoulder width (SW), shoulder height (SH), hip width (HW), hip height (HH), and body length (BL).
  • Mean absolute errors ranged from 0.33 cm to 1.23 cm.
  • Coefficient of determination (R^2) values were between 0.9879 and 0.9973.

Conclusions:

  • The developed CNN model, particularly the modified Xception, offers an accurate, fast, and automated method for pig size and weight estimation.
  • Integration with LabVIEW software enhances its practical application in automated pig farm management.