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

Observational Learning01:12

Observational Learning

163
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
163
High-Level and Low-Level Awareness01:19

High-Level and Low-Level Awareness

262
Controlled processes in human consciousness represent high-alert mental states where individuals deliberately focus their attention on achieving specific goals. Controlled processes can be seen in situations like mastering new technology, where a person might become so absorbed that they ignore surrounding distractions. Such processes involve selective attention, requiring one to concentrate on particular elements of experience while disregarding others. These are governed by executive...
262
Information Processing Approach01:30

Information Processing Approach

33
The information-processing theory of cognitive development centers on fundamental mental processes, including attention, memory, and problem-solving skills. Researchers in this field examine how cognitive abilities, such as working memory, evolve and influence children's overall development. Studies indicate that children with stronger working memory tend to excel in reading comprehension, math, and problem-solving compared to peers with less efficient memory skills. Low working memory is...
33
Fixed Action Patterns01:06

Fixed Action Patterns

15.9K
A fixed action pattern (FAP) is a specific, hard-wired sequence of behaviors that occurs in response to an external stimulus, called a sign stimulus. The behavior is “fixed” because it is essentially unchangeable—proceeding similarly across individuals of a species every time it occurs.
15.9K
Force Classification01:22

Force Classification

1.2K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
1.2K
Masking and Demasking Agents01:19

Masking and Demasking Agents

2.4K
EDTA titrations may necessitate masking and demasking agents to temporarily protect a particular metal ion in a mixture from the EDTA reaction. These agents facilitate the sequential analysis of the metal ions by forming stable complexes with some—but not all—metal ions during certain steps.
There are many masking agents, such as cyanide, fluoride, triethanolamine, thiourea, and 2,3-bis(sulfanyl)propan-1-ol (formerly 2,3-dimercapto-1-propanol), with the masking agent chosen based on...
2.4K

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

Behavior of neural networks in culture suggest that sporadic and genetic forms of Alzheimer's disease may not be equivalent.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2026
Same author

Foveated Retinotopy Improves Classification and Localization in Convolutional Neural Networks.

Vision (Basel, Switzerland)·2026
Same author

DynTex: A real-time generative model of dynamic naturalistic luminance textures.

Journal of vision·2025
Same author

Neuromorphic computing at scale.

Nature·2025
Same author

A dual foveal-peripheral visual processing model implements efficient saccade selection.

Journal of vision·2024
Same author

Stakes of neuromorphic foveation: a promising future for embedded event cameras.

Biological cybernetics·2023
Same journal

A practical design of backdoor trigger under frequency-based orthogonality constraints.

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

EEG fine-grained visual semantic decoding via a multimodal framework.

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

Collaborative-adversarial jailbreaking: A propagation-aware attack framework for multi-agent code generation systems.

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

Theoretical analysis of the denoising autoencoder using Tweedie's formula.

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

Frequency-based cross-attention fusion network for RGB-D salient object detection.

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

HTNet: A self-supervised heterogeneous triple network for multi-modal data.

Neural networks : the official journal of the International Neural Network Society·2026
查看所有相关文章

相关实验视频

Updated: Jun 24, 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

520

一个强大的事件驱动的方法来实现始终在线的对象识别.

Antoine Grimaldi1, Victor Boutin2, Sio-Hoi Ieng3

  • 1Aix-Marseille Universit, Institut de Neurosciences de la Timone, CNRS, Marseille, France.

Neural networks : the official journal of the International Neural Network Society
|June 9, 2024
PubMed
概括
此摘要是机器生成的。

这项研究介绍了一种常在的神经模拟架构,用于实时模式识别. 通过增强基于事件的时间表面层次 (HOTS) 算法,以恒温增益控制和尖端神经网络 (SNN) 集成,它实现了超快的在线对象识别.

关键词:
有效的编码 有效的编码基于事件的计算基于事件的计算.恒常状态 (Homeostasis) 是一种恒常状态.在线分类在线分类模式识别 模式识别 模式识别尖端神经网络的神经网络.视觉 视觉 视觉 视觉 视觉 是一个

更多相关视频

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
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.4K

相关实验视频

Last Updated: Jun 24, 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

520
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
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.4K

科学领域:

  • 神经科学是一个神经科学.
  • 计算机科学 计算机科学
  • 人工智能的人工智能

背景情况:

  • 基于事件的视觉系统使用异步事件捕捉场景动态.
  • 现有的时间表面层次 (HOTS) 算法能够有效地基于事件的模式识别.
  • 神经形相机为先进的人工智能提供生物现实的感官输入.

研究的目的:

  • 为实时模式识别开发一个始终在线的神经模拟架构.
  • 提高基于事件的算法的性能和在线功能.
  • 整合尖端神经网络 (SNN) 以改善时空模式学习.

主要方法:

  • 扩展了时间表面层次 (HOTS) 算法,并提供了恒温增益控制.
  • 开发了一个新的数学形式主义,用于HOTS和尖端神经网络 (SNN) 之间的类比.
  • 实现了一个在线,以事件驱动的分类器,使用神经模拟多项逻辑回归.

主要成果:

  • 在模式识别任务中实现一致的性能增加.
  • 启用完全在线,事件驱动的模式识别功能.
  • 通过事件对事件的分类来证明超快的对象识别.

结论:

  • 增强的神经模拟架构为事件驱动的模式识别提供了卓越的性能.
  • 结合SNN原则,为实时应用推进了生物现实的AI.
  • 在各种数据集中验证了效率,展示了超快速对象识别的潜力.