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

A Novel Machine Learning Approach for Predicting Prognosis of SFTS Patients in the Early Stages of Disease.

The Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale·2026
Same author

Distinct Longitudinal Trajectories of SLEDAI-2K Scores Predict Prognosis in Systemic Lupus Erythematosus Based on Group-Based Trajectory Modeling.

Journal of immunology research·2026
Same author

T Follicular Helper Cell Immune Signatures Associated With Disease Severity in Severe Fever With Thrombocytopenia Syndrome.

Journal of immunology research·2026
Same author

Integration of SFTSV Viral Load, Age, and Double-Negative B-Cells as Prognostic Biomarkers for Severe Fever With Thrombocytopenia Syndrome Outcomes.

Journal of immunology research·2026
Same author

Rare ANA patterns and their clinical correlates: a retrospective large-cohort study.

Clinical chemistry and laboratory medicine·2026
Same author

Longitudinal, Multi-Cycle Evaluation of Passive Function Improvement in People with Arm Spasticity Treated with Botulinum Toxin A.

Toxins·2026
Same journal

Logic, inference, understanding: cross-domain generalization for generative language models.

Frontiers in artificial intelligence·2026
Same journal

Label tree semantic losses for rich multi-class medical image segmentation.

Frontiers in artificial intelligence·2026
Same journal

Score-based generative diffusion models to synthesize full-dose FDG brain PET from MRI in epilepsy patients.

Frontiers in artificial intelligence·2026
Same journal

Resource-efficient retrieval-augmented question answering for the Indian Lok Sabha dataset.

Frontiers in artificial intelligence·2026
Same journal

Violation detection in power operation sites based on multi-scale detection and few-shot learning.

Frontiers in artificial intelligence·2026
Same journal

Deep reinforcement learning-based reversible medical image encryption framework for secure IoMT environments.

Frontiers in artificial intelligence·2026
查看所有相关文章

相关实验视频

Updated: May 7, 2025

Computer-based Multitaper Spectrogram Program for Electroencephalographic Data
04:13

Computer-based Multitaper Spectrogram Program for Electroencephalographic Data

Published on: November 13, 2019

12.0K

使用多谱图热图分析解释音乐乐器识别CNN模型:一项初步研究

Rujia Chen1, Akbar Ghobakhlou1, Ajit Narayanan1

  • 1Computer Science and Software Engineering Department, Auckland University of Technology, Auckland, New Zealand.

Frontiers in artificial intelligence
|January 2, 2025
PubMed
概括
此摘要是机器生成的。

这项研究使用卷积神经网络 (CNN) 评估了用于乐器识别的光谱图. 梅尔频率塞普斯特拉系数 (MFCC) 和Log-Mel光谱图在分类十种仪器方面被证明是最有效的.

关键词:
卷积神经网络是一种卷积神经网络.功能提取 特性提取功能地图的特征地图.热图 热图 热图 热图音乐信息检索和检索音乐乐器识别功能 音乐乐器识别功能模式识别 模式识别 模式识别分析频谱图的分析.

更多相关视频

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

4.5K
Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.3K

相关实验视频

Last Updated: May 7, 2025

Computer-based Multitaper Spectrogram Program for Electroencephalographic Data
04:13

Computer-based Multitaper Spectrogram Program for Electroencephalographic Data

Published on: November 13, 2019

12.0K
Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

4.5K
Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.3K

科学领域:

  • 音乐信息检索 (MIR) 是一种音乐信息检索技术.
  • 机器学习 机器学习
  • 音频信号处理 音频信号处理

背景情况:

  • 音乐乐器识别对于MIR至关重要,但由于信号的复杂性而具有挑战性.
  • 卷积神经网络 (CNN) 越来越多地用于音频分类任务.

研究的目的:

  • 为了比较各种谱图表示用于乐器识别的有效性.
  • 通过统计和视觉分析来评估特征的重要性和模型可解释性.

主要方法:

  • 利用CNN从NSynth数据库中对10种乐器进行分类.
  • 分析了短时间里埃变换 (STFT),Log-Mel,MFCC,Chroma,光谱对比和涅茨光谱图.
  • 采用视觉热图分析和统计指标 (差异平均值,KL分歧,JS分歧,地球移动器距离) 进行解释.

主要成果:

  • 在仪器分类中,MFCC和Log-Mel光谱图通常表现优于其他表示.
  • 不同的光谱图揭示了捕捉特定仪器特征的独特优势.
  • 分析提供了关于每个特征类型的区分能力的见解.

结论:

  • 谱图的选择显著影响了乐器识别性能.
  • MFCC和Log-Mel频谱为基于CNN的仪器分类提供了一个强大的方法.
  • 该研究增强了对优化MIR系统和改善模型解释性的理解.