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

Nonconscious Mimicry01:13

Nonconscious Mimicry

4.5K
Nonconscious mimicry occurs when individuals alter their mannerisms to match the behaviors and expressions of those nearby, without intention.
4.5K
Ethics in Research01:56

Ethics in Research

22.8K
Today, scientists agree that good research is ethical in nature and is guided by a basic respect for human dignity and safety. However, this has not always been the case. Modern researchers must demonstrate that the research they perform is ethically sound.
22.8K

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

An Investigation of Shelter Workers' Perspectives on the Assessment and Management of Unowned Cat Welfare in the United Kingdom.

Animals : an open access journal from MDPI·2026
Same author

Analysis of human-oriented facial signals of the domestic dog using eye tracker technology.

Frontiers in veterinary science·2026
Same author

Guidance for protocol content and reporting of dog-assisted interventions in randomised controlled trials: explanation and elaboration of the SPIRIT 2025 and CONSORT 2025 extensions.

BMC medical research methodology·2026
Same author

A scoping review of neuroendocrinological biomarkers with potential for use in equine behavioral medicine practice.

BMC veterinary research·2026
Same author

Predicting guide dog career success using machine learning and large language models.

Scientific reports·2026
Same author

Reporting of dog-assisted intervention trials: extension of the SPIRIT 2025 and CONSORT 2025 statement.

BMC medical research methodology·2026

相关实验视频

Updated: May 10, 2025

Observational Fear as a Model of Affective Empathy in Mice
04:14

Observational Fear as a Model of Affective Empathy in Mice

Published on: November 22, 2024

415

一个基于细分的框架,用于动物情感计算中的可解释性.

Tali Boneh-Shitrit1, Lauren Finka2, Daniel S Mills3

  • 1Information Systems Department, University of Haifa, Haifa, Israel.

Scientific reports
|April 21, 2025
PubMed
概括

这项研究引入了一个新的框架来量化动物情感计算中的可解释性. 它有助于评估深度学习模型是否专注于相关的动物身体部位,以准确识别情绪.

更多相关视频

Automated Interactive Video Playback for Studies of Animal Communication
07:21

Automated Interactive Video Playback for Studies of Animal Communication

Published on: February 9, 2011

13.3K
Profiling Maternal Behavior Responses During Whole-Brain Imaging
07:12

Profiling Maternal Behavior Responses During Whole-Brain Imaging

Published on: January 24, 2025

561

相关实验视频

Last Updated: May 10, 2025

Observational Fear as a Model of Affective Empathy in Mice
04:14

Observational Fear as a Model of Affective Empathy in Mice

Published on: November 22, 2024

415
Automated Interactive Video Playback for Studies of Animal Communication
07:21

Automated Interactive Video Playback for Studies of Animal Communication

Published on: February 9, 2011

13.3K
Profiling Maternal Behavior Responses During Whole-Brain Imaging
07:12

Profiling Maternal Behavior Responses During Whole-Brain Imaging

Published on: January 24, 2025

561

科学领域:

  • 动物行为分析 动物行为分析
  • 机器学习的可解释性
  • 情感计算是一种情感计算.

背景情况:

  • 深度学习模型对于动物影响的识别至关重要,但缺乏解释性.
  • 目前的可解释性方法,如突出性地图,主要是定性.
  • 量化可解释性对于动物福利研究的信任和采用至关重要.

研究的目的:

  • 提出一个框架,以提高和量化动物情感计算中的可解释性.
  • 评估和比较来自深度学习模型的视觉解释.
  • 评估显著性地图与语义上有意义的动物区域的对齐.

主要方法:

  • 开发了一个定量评分机制来比较突出性地图.
  • 专注于评估基于预定义的语义区域的视觉解释.
  • 利用了三个数据集来识别猫,马和狗的疼痛和情绪.

主要成果:

  • 拟议的框架允许对可解释性方法进行系统的,可测量的比较.
  • 突出地图始终强调眼睛区域是数据集中最重要的.
  • 展示了可解释性框架的潜力,以揭示AI如何解释动物情感状态.

结论:

  • 该框架为开发和评估动物情感计算分类器提供了质量指标.
  • 强调着重关注生物相关的语义区域对于模型可解释性的重要性.
  • 为建立信任和推进人工智能驱动的动物福利和健康研究提供了一种新的方法.