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

Glaucoma: Overview01:25

Glaucoma: Overview

630
Glaucoma is an eye condition characterized by increased intraocular pressure that damages the retina and optic nerve, leading to irreversible blindness if left untreated. The human eye has various components, including the cornea, iris, pupil, lens, and optic nerve. Aqueous humor is secreted by the epithelium of the ciliary body in the posterior chamber and flows through the trabecular meshwork and canal of Schlemm, maintaining normal intraocular pressure. The trabecular meshwork and the canal...
630
Angle Closure Glaucoma: Treatment01:28

Angle Closure Glaucoma: Treatment

577
Angle-closure glaucoma, or closed-angle glaucoma, is an eye condition where the iris bulges out and blocks the iridocorneal angle, resulting in a buildup of aqueous humor and increased intraocular pressure. Immediate medical attention is necessary due to the sudden onset of symptoms. The treatment for angle-closure glaucoma includes short-term and long-term approaches. Short-term treatment involves using eye drops like pilocarpine to lower intraocular pressure by increasing aqueous humor...
577
Open Angle Glaucoma: Treatment01:27

Open Angle Glaucoma: Treatment

481
In open-angle glaucoma, the iridocorneal angle remains open, but the trabecular meshwork becomes stiff, slowing down the outflow of aqueous humor. This causes a buildup of aqueous humor in the anterior chamber, leading to a sudden increase in intraocular pressure. The treatment for open-angle glaucoma focuses on reducing the elevated intraocular pressure by either decreasing the secretion of aqueous humor or increasing its outflow.
Drugs such as carbonic anhydrase inhibitors, α2- and...
481
Classification of Systems-II01:31

Classification of Systems-II

183
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
183
Classification of Systems-I01:26

Classification of Systems-I

221
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
221
Aggregates Classification01:29

Aggregates Classification

350
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
350

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

Classification of pulmonary disorders using pulmonary network with explainable AI framework from chest multi-modal images.

Scientific reports·2026
Same author

Schizophrenia detection via lobe-wise and overall EEG features using VMD and bayesian-optimized machine learning models.

Frontiers in neuroscience·2026
Same author

Lobe-wise cognitive load detection using empirical Fourier decomposition and optimized machine learning.

Frontiers in physiology·2026
Same author

Detection of cognitive load using EEG signal and lifting wavelet transform with specific lead selection.

Biomedical physics & engineering express·2025
Same author

A systematic review of EEG based automated schizophrenia classification through machine learning and deep learning.

Frontiers in human neuroscience·2024
Same author

Automated detection of myocardial infarction using binary Harry Hawks feature selection and ensemble KNN classifier.

Computer methods in biomechanics and biomedical engineering·2023

相关实验视频

Updated: Jul 25, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

585

使用预训练的卷积神经网络和以投票为基础的分类器融合,进行多阶段绿眼的分类.

Vijaya Kumar Velpula1, Lakhan Dev Sharma1

  • 1School of Electronics Engineering, VIT-AP University, Amaravati, Andhra Pradesh, India.

Frontiers in physiology
|June 29, 2023
PubMed
概括

这项研究开发了一种使用深层卷积神经网络 (CNN) 和分类器融合的自动化玻璃眼瘤检测系统. 该系统通过 fundus 图像实现了高精度的早期玻璃眼瘤检测,优于现有方法.

科学领域:

  • 眼科医生 眼科 眼科
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 玻璃眼是导致不可逆转失明的主要原因.
  • 早期检测对于有效的绿眼病管理至关重要.
  • 目前的诊断方法耗时,可能不准确.

研究的目的:

  • 开发一种用于早期发现青光眼的自动化系统.
  • 使用深度学习模型来分类青光眼的各个阶段.
  • 通过分类器融合来提高诊断的准确性.

主要方法:

  • 使用了五个预训练的深卷积神经网络 (CNN) 模型:ResNet50,AlexNet,VGG19,DenseNet-201和Inception-ResNet-v2.
  • 采用基于最大投票的分类器融合方法.
  • 在四个公共数据集上验证了模型:ACRIMA,RIM-ONE,哈佛数据集 (HVD) 和Drishti.

主要成果:

  • 在ACRIMA数据集上获得了99.57%的准确性和1.0的AUC.
  • 在数据集中表现出高性能,AUC为0.97 (HVD),0.90 (Drishti) 和0.95 (RIM-ONE).
  • 拟议的模型在早期格劳科马分类方面表现优于最先进的方法.
关键词:
分类器 聚变 融合 分类器卷积神经网络是一种卷积神经网络.深度学习是一种深度学习.图片来源: 基金图像基金混合型 混合型 混合型 混合型转移学习转移学习

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

2.8K
Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping
07:11

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

1.6K

相关实验视频

Last Updated: Jul 25, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

585
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

2.8K
Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping
07:11

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

1.6K

结论:

  • 自动化青光眼分类模型有效地实现了早期青光眼检测.
  • 预训练CNN和分类器融合的组合提供了卓越的性能.
  • 该系统有望提高青光眼诊断的准确性和效率.