Jove
Visualize
联系我们

相关概念视频

Inductive Reasoning00:59

Inductive Reasoning

60.2K
Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. It is uncertain and operates in degrees to which the conclusions are credible. As such, inductive arguments can be weak or strong, rather than valid or invalid, and conclusions can be used to formulate testable, falsifiable hypotheses.
Inductive reasoning is common in descriptive science. A life scientist makes observations and records them. This data can be qualitative or...
60.2K
Heuristics01:21

Heuristics

81
Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
81
Deductive Reasoning01:16

Deductive Reasoning

55.1K
Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning, which means that it uses a general principle or law to predict specific results. From those general principles, a scientist can deduce and predict the specific results that would be valid as long as the general principles are valid.
For example, a researcher can deduce specific predictions...
55.1K
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

107
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
107
Reason and Intuition01:37

Reason and Intuition

6.4K
The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
6.4K
Cause and Effect01:53

Cause and Effect

10.9K
While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
10.9K

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

DARE: An Explainable AI-visualization Framework for Ill-defined Decision Making.

IEEE transactions on visualization and computer graphics·2026
Same author

MAPLE: Self-Supervised Learning-Enhanced Nonlinear Dimensionality Reduction for Visual Analysis.

IEEE transactions on visualization and computer graphics·2026
Same author

Topology-Based Visualization Techniques for Scientific Data Exploration.

IEEE computer graphics and applications·2025
Same author

Present and Future of Everyday-Use Augmented Reality Eyeglasses.

IEEE computer graphics and applications·2025
Same author

Toward Constructing Frameworks for Task- and Design-Optimized Visualizations.

IEEE computer graphics and applications·2024
Same author

Visualization for Trust in Machine Learning Revisited: The State of the Field in 2023.

IEEE computer graphics and applications·2024
Same journal

Graph Pattern Matching based reassembly - 3DGPM.

IEEE computer graphics and applications·2026
Same journal

Making Learning Visible: Turning Public Engagement into Evidence for Academic Learning.

IEEE computer graphics and applications·2026
Same journal

LlymX: Multimodal LLM-Augmented XR for Context-Aware Information Access.

IEEE computer graphics and applications·2026
Same journal

Dynamic Gaussian-Based Digital Twin Reconstruction of Articulated Multi-Joint Objects.

IEEE computer graphics and applications·2026
Same journal

Steiner and Poisson Traversal Initializations: Initial Curve Optimization for Geometric Flow-based Surface Filling.

IEEE computer graphics and applications·2026
Same journal

Insight Into the Insight Toolkit.

IEEE computer graphics and applications·2026
查看所有相关文章
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

相关实验视频

Updated: Jun 14, 2025

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
10:58

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

10.1K

视觉分析用于可解释和可靠的人工智能.

Angelos Chatzimparmpas, Sumanta N Pattanaik

    IEEE computer graphics and applications
    |June 12, 2025
    PubMed
    概括
    此摘要是机器生成的。

    视觉分析 (VA) 通过将AI模型与交互式可视化相结合,增强对人工智能 (AI) 系统的信任. 这种方法使专家能够改进人工智能模型,提高其可靠性和在医疗保健等关键应用中采用.

    更多相关视频

    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
    03:14

    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

    Published on: December 6, 2024

    519
    Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios
    06:02

    Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios

    Published on: October 6, 2020

    2.2K

    相关实验视频

    Last Updated: Jun 14, 2025

    Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
    10:58

    Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

    Published on: January 2, 2011

    10.1K
    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
    03:14

    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

    Published on: December 6, 2024

    519
    Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios
    06:02

    Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios

    Published on: October 6, 2020

    2.2K

    科学领域:

    • 人工智能的人工智能
    • 人与计算机的交互
    • 数据可视化 数据可视化

    背景情况:

    • 智能系统对于解决复杂问题至关重要,包括医疗诊断,但它们的不透明性阻碍了专家的信任和采用.
    • 人工智能系统缺乏透明度,导致可靠性和融入关键领域的挑战,尽管人工智能有潜力改善结果和减少经济负担.
    • 视觉分析 (VA) 提供了一种将AI与交互式可视化集成的方法,使专家能够提供意见并弥合AI和人类理解之间的差距.

    研究的目的:

    • 定义,分类和探索视觉分析 (VA) 解决方案如何促进对人工智能 (AI) 系统的信任.
    • 为创新的可视化提供一个设计空间,以提高AI的透明度和可用性.
    • 介绍开发的VA仪表板的概述,支持人工智能管道的各个阶段.

    主要方法:

    • 文献综述和AI中VA的概念框架开发.
    • 探索VA技术,以提高AI模型的透明度和可解释性.
    • 开发和展示VA仪表板用于AI管道阶段:数据处理,特征工程,超参数调整,模型理解,调试,改进和比较.

    主要成果:

    • 通过交互式可视化,VA有效地弥合了AI预测和人类专业知识之间的差距.
    • 为创新的VA解决方案提出了一个设计空间,为开发信任建设工具提供了一个结构化的方法.
    • 开发的VA仪表板展示了在整个AI生命周期中支持关键任务的实际应用,从数据准备到模型评估.

    结论:

    • 视觉分析是一种强大的方法,可以增加信任,并促进人工智能系统在各种领域的采用,特别是在医疗保健领域.
    • 交互式可视化使领域专家能够理解,改进和验证人工智能模型,从而实现更可靠和值得信赖的智能系统.
    • 拟议的VA设计空间和展示的仪表板为未来开发透明和以用户为中心的AI解决方案提供了基础.