Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

New records of the colonial chrysophyte <i>Urostipulosphaeraarticulata</i> (Chrysophyceae, Ochromonadales) in China.

Biodiversity data journal·2025
Same author

Nanomaterials Mediated Enhancement of CAR-T for HCC: Revolutionizing Immunotherapy Strategies.

International journal of nanomedicine·2025
Same author

Generative prediction of real-world prevalent SARS-CoV-2 mutation with in silico virus evolution.

Briefings in bioinformatics·2025
Same author

Validation of Targeted Relationships of Novel circRNA803/lncRNA MSTRG.19726-oar-let-7a-CPEB1 ceRNA Networks, Key to Follicle Development in Single-Litter and Multi-Litter Sheep Based on Whole-Transcriptome Sequencing.

International journal of molecular sciences·2025
Same author

The Relationship between Renal Interstitial Vasculopathy and Clinical and Prognosis of Patients with Lupus Nephritis.

Kidney diseases (Basel, Switzerland)·2025
Same author

Letter to the Editor: Comparison of transcatheter tricuspid valve intervention and medical therapy in patients with tricuspid regurgitation.

International journal of surgery (London, England)·2025
Same journal

Novel Parent Survey Measures Sensory Behaviors Incorporating Sensory Modality and Stimulus Intensity.

Heliyon·2026
Same journal

Expression of concern: "SQSTM1/p62 promotes the progression of gastric cancer through epithelial-mesenchymal transition" [Heliyon 10 (2024) e24409].

Heliyon·2026
Same journal

Expression of concern: "TL1A promotes metastasis and EMT process of colorectal cancer" [Heliyon 10 (2024) e24392].

Heliyon·2026
Same journal

Expression of concern: "Factors affecting timing of surgery following neoadjuvant chemoradiation for esophageal cancer" [Heliyon 9 (2023) e23212].

Heliyon·2026
Same journal

Expression of concern: "On stratified single-valued soft topogenous structures" [Heliyon 10 (2024) e27926].

Heliyon·2026
Same journal

Expression of concern: "Artifact removal and motor imagery classification in EEG using advanced algorithms and modified DNN" [Heliyon 10 (2024) e27198].

Heliyon·2026
查看所有相关文章

相关实验视频

Updated: Jun 20, 2025

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

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.0K

基于图像数据可视化和深度学习的教育资源管理.

Xudong Liu1

  • 1University of the Cordilleras, Baguio City, 2600, Philippines.

Heliyon
|July 23, 2024
PubMed
概括
此摘要是机器生成的。

这项研究使用深度学习和图像可视化来增强教育资源管理系统 (ERMS). 优化的卷积神经网络 (CNN) 提高了教育资源管理的准确性和效率.

关键词:
卷积神经网络是一种卷积神经网络.数据可视化数据可视化教育资源管理教育资源管理功能要求 功能要求图片 图片 图片 图片 图片性能比较 性能比较

更多相关视频

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.7K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.7K

相关实验视频

Last Updated: Jun 20, 2025

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

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.0K
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.7K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.7K

科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 教育技术的教育技术

背景情况:

  • 教育资源管理系统 (ERMS) 在准确定位和高效利用方面面临着挑战.
  • 整合先进技术对于现代化教育管理至关重要.

研究的目的:

  • 通过整合图像数据可视化和深度学习卷积神经网络 (CNN) 来优化ERMS.
  • 解决ERMS内部资源定位中的不准确性和资源利用中的低效性.

主要方法:

  • 分析ERMS在教育和教学中的作用.
  • 在ERMS中图像数据可视化和CNN的应用和挑战.
  • 优化CNN的模型和系统架构.

主要成果:

  • 优化的CNN模型在Mnist数据集上达到98.1%的准确性,在cifar-10数据集上达到98.3%.
  • 对于优化模型,运行时间减少到640.4s.
  • 满足了系统功能要求,验证了模型的可行性和合理性.

结论:

  • 提议的优化ERMS模型具有很高的实用价值.
  • 与传统模型相比,在性能指标上观察到显著的改进.
  • 这项研究为优化ERMS的CNN和图像数据可视化提供了洞察力.