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

Methods of Classification and Identification01:28

Methods of Classification and Identification

209
Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...
209
Classification of Neurotransmitters01:30

Classification of Neurotransmitters

3.6K
Neurotransmitters play a crucial role in the communication between neurons in the autonomic nervous system. Neurons in the autonomic nervous system can be cholinergic or adrenergic depending on the neurotransmitters synthesized. Cholinergic neurons use acetylcholine as their primary neurotransmitter. This includes all the preganglionic fibers of the sympathetic and pre- and postganglionic fibers of the parasympathetic nervous systems. In addition, neurons of the somatic nervous system also use...
3.6K

You might also read

Related Articles

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

Sort by
Same author

Wellbore stability model for argillaceous limestone - claystone thin interbeds under synergistic effect of fluctuating pressure -hydration.

Scientific reports·2025
Same author

Study on the γ/γ' Eutectic Inhomogeneity of a Novel 3rd Generation Nickel-Based Single-Crystal Superalloy Casting.

Materials (Basel, Switzerland)·2025
Same author

Genetic Diversity of Fresh Maize Germplasm Revealed by Morphological Traits and SSR Markers.

Genes·2025
Same author

Genome-Wide Association Analysis of Fresh Maize.

International journal of molecular sciences·2025
Same author

An Annealing Strategy for Inhibiting Recrystallization in Nickel-Based Single-Crystal Superalloys.

Materials (Basel, Switzerland)·2025
Same author

Effect of Solidification Direction on the Freckle Formation in Single-Crystal Superalloy Castings.

Materials (Basel, Switzerland)·2025

Related Experiment Video

Updated: Sep 17, 2025

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

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.4K

Corn variety identification based on improved EfficientNet lightweight neural network.

Jinpu Xu1,2, Jinhao Lan3, Guangjie Lv4

  • 1College of Animation and Communication, Qingdao Agricultural University, Qingdao, China.

Frontiers in Plant Science
|July 4, 2025
PubMed
Summary

This study introduces SCD_EFTNet, an AI model for identifying corn ear varieties. This deep learning approach enhances seed authenticity screening, improving crop yields and market value.

Keywords:
CBAMEfficientNetB0classificationcorn eardilated convolutionvariety identification

More Related Videos

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

1.6K
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.7K

Related Experiment Videos

Last Updated: Sep 17, 2025

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

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.4K
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

1.6K
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.7K

Area of Science:

  • Agricultural Science
  • Computer Vision
  • Machine Learning

Background:

  • Corn seed authenticity is vital for crop yield and economic value.
  • Effective screening of corn ears is crucial for seed processing and intellectual property protection.
  • Current methods for corn ear identification may lack efficiency and accuracy.

Purpose of the Study:

  • To develop an intelligent system for classifying and identifying corn ear varieties using deep learning.
  • To propose an improved EfficientNet lightweight model for enhanced corn ear image analysis.
  • To protect intellectual property rights of corn varieties through accurate identification.

Main Methods:

  • Collected a dataset of 6529 RGB images of corn ears from five varieties.
  • Developed the SCD_EFTNet model by modifying EfficientNetB0, incorporating CBAM attention and dilation convolution.
  • Utilized the Swish activation function to improve gradient transfer stability.

Main Results:

  • The SCD_EFTNet model demonstrated superior performance over mainstream models in Recall, Precision, and mAP.
  • Achieved a mean Average Precision (mAP) of 98.11% in corn ear classification.
  • Showcased significant improvements in inference time compared to existing models.

Conclusions:

  • Phenotypic characteristics of corn ears are effective for classifying and identifying different varieties.
  • The proposed SCD_EFTNet model offers a reliable and efficient solution for intelligent corn ear sorting.
  • This research provides a valuable reference for automated agricultural processes and quality control.