人工智能从视频中识别并学习预测行为模式

 2个月前     57  
人工智能从视频中识别并学习预测行为模式

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人工智能从视频中识别并学习预测行为模式

卡内基梅隆大学、波恩大学医院和波恩大学的研究人员创建了一个名为A-SOiD的开源平台,可以通过视频学习和预测用户定义的行为。这项研究的结果现已发表在《自然方法》杂志上

与许多人工智能(AI)程序不同,a-SOiD不是一个黑匣子。相反,研究人员允许该程序重新学习它做错了什么。他们首先用数据集的一小部分训练程序,重点关注程序较弱的信念。如果程序不确定,算法将加强对训练数据的信任

因为A-SOiD被教导要关注算法的不确定性,而不是对所有数据一视同仁,卡内基梅隆大学最近的博士校友Alex Hsu说,它避免了其他人工智能模型中常见的偏见

因为A-SOiD是以有监督的方式训练的,所以它可以非常精确。如果给它一个数据集,它可以确定一个人的正常颤抖和帕金森病患者的颤抖之间的差异。它也是他们两年前发布的无监督行为分割平台B-SOiD的补充方法。

人工智能工具公正地对待数据集中的每一个类别

除了是一个有效的程序,A-SOiD是高度可访问的,能够在普通计算机上运行,并在GitHub上作为开源提供

A-SOiD科学界的每个人都可以访问

波恩大学医院的波恩大学博士后研究员Jens Tillmann表示,向所有研究人员开放该项目的想法是其影响的一部分

Yttri和波恩大学医院首席研究员、波恩大学跨学科研究领域(TRA)“生命与健康”成员Martin K.Schwarz,计划在他们自己的实验室中使用A-SOiD来进一步研究大脑和行为之间的关系。Yttri计划将A-SOiD与其他工具结合起来研究自发行为的神经机制。Schwartz将A-SOiD与其他行为模式相结合,对社交互动中的已知行为进行细粒度分析

Jens Tillmann, a postdoctoral researcher from the University of Bonn at the University Hospital Bonn, said that the idea of having this program open to all researchers was part of its impact.

"This project wouldn't have been possible without the open science mindset that both of our labs, but also the entire community of neuroethology have shown in recent years," Tillmann said. "I am excited to be part of this community and look forward to future collaborative projects with other experts in the field."

Yttri and Martin K. Schwarz, principal investigator at the University Hospital Bonn and member of the Transdisciplinary Research Areas (TRA) "Life & Health" at the University of Bonn, plan on using A-SOiD in their own labs to further investigate the relationship between the brain and behavior. Yttri plans to use A-SOiD in conjunction with other tools to investigate the neural mechanisms underlying spontaneous behaviors. Schwartz will use A-SOiD in conjunction with other behavioral modalities for a fine-grained analysis of known behaviors in social interactions.

Both Yttri and Schwarz said they hope that A-SOiD will be used by other researchers across disciplines and countries.

"A-SOiD is an important development allowing an AI-based entry into behavioral classification and thus an excellent unique opportunity to better understand the causal relationship between brain activity and behavior," Schwarz said. "We also hope that the development of A-SOiD will serve as an efficient trigger for forthcoming collaborative research projects focusing on behavioral research in Europe but also across the Atlantic."

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