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

Neural Circuits01:25

Neural Circuits

1.6K
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
1.6K

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

EmbBERT: Attention under 2 MB memory.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Big Data, Machine Learning, and Personalization in Health Systems: Ethical Issues and Emerging Trade-Offs.

Science and engineering ethics·2025
Same author

Mixture-of-experts graph transformers for interpretable particle collision detection.

Scientific reports·2025
Same author

Micrographia in Parkinson's Disease: Automatic Recognition through Artificial Intelligence.

Movement disorders clinical practice·2025
Same author

Adaptive token selection for scalable point cloud transformers.

Neural networks : the official journal of the International Neural Network Society·2025
Same author

Position: Topological Deep Learning is the New Frontier for Relational Learning.

Proceedings of machine learning research·2025
Same journal

Granular Ball-Based Noise-Resistant Fuzzy Multineighborhood Feature Selection via Label Enhancement and Feature Graph.

IEEE transactions on neural networks and learning systems·2026
Same journal

Fighting Evolving Spam With ARTMAP Models: A Noise-Resilient Online Detection Framework.

IEEE transactions on neural networks and learning systems·2026
Same journal

HyperSAT: Unsupervised Hypergraph Neural Networks for Weighted MaxSAT Problems.

IEEE transactions on neural networks and learning systems·2026
Same journal

Negation of Basic Belief Assignment in Multisource Information Fusion on Dempster-Shafer Theory With Applications in Pattern Classification.

IEEE transactions on neural networks and learning systems·2026
Same journal

Intervention Feasible Region and Driver Risk Capacity Aware Human-Machine Collaborative Safe Trajectory Planning.

IEEE transactions on neural networks and learning systems·2026
Same journal

A Unified Differential Denoising Learning Framework With a Pre-Trained Model and Fuzzy Graph Networks for Drug-Drug Interaction Prediction.

IEEE transactions on neural networks and learning systems·2026
查看所有相关文章

相关实验视频

Updated: Sep 14, 2025

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.4K

纳科斯:神经架构 搜索硬件受限制的早期退出神经网络

Matteo Gambella, Jary Pomponi, Simone Scardapane

    IEEE transactions on neural networks and learning systems
    |July 21, 2025
    PubMed
    概括
    此摘要是机器生成的。

    本研究介绍了NACHOS,这是一种用于设计高效早期退出神经网络 (EENNs) 的新型神经架构搜索框架. NACHOS自动化了EENN的联合设计,在硬件限制下优化了准确性和计算效率.

    更多相关视频

    Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits
    10:32

    Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

    Published on: April 15, 2015

    8.6K
    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

    642

    相关实验视频

    Last Updated: Sep 14, 2025

    Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
    11:18

    Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

    Published on: March 2, 2015

    10.4K
    Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits
    10:32

    Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

    Published on: April 15, 2015

    8.6K
    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

    642

    科学领域:

    • 人工智能的人工智能
    • 计算机科学 计算机科学

    背景情况:

    • 早期退出神经网络 (EENNs) 通过在中间阶段进行预测来提供效率和有效性.
    • 手动设计EENN是复杂的,耗时的,并且需要专家知识来实现最佳配置.
    • 使用神经架构搜索 (NAS) 自动化EENN设计是一个活跃的研究领域.

    研究的目的:

    • 介绍NACHOS,这是第一个用于设计硬件限制的EENN的NAS框架.
    • 为了实现EENN骨干和早期退出分类器 (EEC) 的联合优化.
    • 为了满足准确性和多重积累 (MAC) 操作的限制.

    主要方法:

    • 开发了NACHOS,这是一个NAS框架,用于联合骨干和EEC设计.
    • 将硬件约束 (准确性和MAC操作) 纳入搜索过程中.
    • 确定了帕雷托最佳EENN解决方案,平衡精度和计算成本.

    主要成果:

    • 纳科斯成功地设计了与最先进的模型相匹配的EENN.
    • 该框架提供了一组可接受的帕雷托最佳解决方案.
    • 研究了辅助分类器的新型规范化技术.

    结论:

    • NACHOS提供了一种完全自动化的方法来设计高效的EENNs.
    • 该框架有效平衡硬件部署的准确性和计算效率.
    • 未来的工作包括进一步探索EENN优化规范化策略.