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

Tagging and Fusion Proteins01:24

Tagging and Fusion Proteins

6.6K
Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
6.6K
Stereotype Content Model02:16

Stereotype Content Model

13.9K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
13.9K
Classification of Signals01:30

Classification of Signals

381
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
381
Empathy02:34

Empathy

9.5K
Some researchers suggest that altruism operates on empathy. Empathy is the capacity to understand another person’s perspective, to feel what he or she feels. An empathetic person makes an emotional connection with others and feels compelled to help (Batson, 1991). Empathy can be expressed in several ways, including cognitive, affective, and motor. 
9.5K
Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

6.4K
Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
6.4K
Prediction Intervals01:03

Prediction Intervals

2.2K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
2.2K

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

Dynamic central-peripheral balance in brain-muscle interactions reveals motor impairment in post-stroke hemiplegia: an exploratory study.

Cognitive neurodynamics·2026
Same author

Effectiveness of transcutaneous spinal direct current stimulation combined with exercise training in patients with anterior cruciate ligament reconstruction: study protocol for a randomized controlled trial.

Trials·2026
Same author

Effects of repetitive transcranial magnetic stimulation on neuropathic pain in patients with spinal cord injury: a systematic review and meta-analysis of randomized controlled trials.

Frontiers in neurology·2026
Same author

Characteristics of corticospinal excitability following anterior cruciate ligament reconstruction and immediate effects of transcutaneous spinal direct current stimulation: A preliminary study.

The Knee·2026
Same author

Numerical simulation-based study on the response of urban drainage networks to flooding and road risk in typical plain city.

Journal of environmental management·2026
Same author

Feature-enhanced hybrid-optimized convolutional neural network-long short-term memory framework for real-time early warning of sudden total suspended solids pollution events in riverine waters.

Journal of environmental management·2026
Same journal

Anchor-based disentanglement framework for incremental multi-view clustering.

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

Complex-valued amplitude-phase interference modeling for adversarially robust classification.

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

TraNce: Type-aware hypergraph neural network with biological mediators for drug repositioning.

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

Decentralized ADMM for factorization-based Low-rank matrix estimation.

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

Memristive neuromorphic circuit design inspired by the neural mechanisms of conditioned fear.

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

Q-learning based asynchronous Boolean control networks stabilization with data loss.

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: May 28, 2025

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

4.6K

TF-BERT:基于张量器的融合BERT用于多式联网情绪分析.

Jingming Hou1, Nazlia Omar1, Sabrina Tiun1

  • 1Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.

Neural networks : the official journal of the International Neural Network Society
|February 12, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了基于张量器的融合BERT (TF-BERT) 用于多式联络情绪分析,克服了仅处理两个模式的局限性. TF-BERT通过同时处理三种模式来提高准确性来增强情绪数据融合.

关键词:
模式相互作用 模式相互作用多式联络情绪分析多式联络情绪分析预先训练的语言模型.变压器变压器变压器

更多相关视频

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.4K
Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.0K

相关实验视频

Last Updated: May 28, 2025

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

4.6K
Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.4K
Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.0K

科学领域:

  • 人工智能的人工智能
  • 自然语言处理自然语言处理.
  • 计算机视觉 计算机视觉

背景情况:

  • 单模式情感分析与现实世界的复杂性作斗争.
  • 现有的用于多式联络情绪分析的变压器模型仅限于同时处理两个模式.
  • 这种限制导致信息交换不足和情绪数据的潜在损失.

研究的目的:

  • 提出一种新的基于电压器的融合BERT (TF-BERT) 模型,以解决传统交叉模式变压器模型的局限性.
  • 在多式联络情绪分析中增强信息交换和情绪数据表示.
  • 允许同时处理三种模式,以便进行更全面的分析.

主要方法:

  • 开发了集成到BERT的基于张量器的跨模融合 (TCF) 模块.
  • 引入了基于子的交叉模式变压器 (TCT) 模块,用于同时处理三种模式.
  • 将TCF嵌入到BERT的变压器的多层中,以实现渐进,动态的模式补充.

主要成果:

  • 在大多数指标中,TF-BERT在CMU-MOSI和CMU-MOSEI数据集上取得了最先进的结果.
  • 废弃性研究证实了TCF和TCT模块的有效性.
  • 该模型在逐步整合和捕捉所有模式的复杂情感互动方面表现出卓越的表现.

结论:

  • TF-BERT有效地克服了多式联运情绪分析中传统模型的局限性.
  • 拟议的TCF和TCT模块显著改善了信息交换和情感表现.
  • TF-BERT提供了一种更强大,更全面的方法来分析多式联络数据中的复杂情感互动.