澄清DNN作为人类视觉模型的地位
Jeffrey S Bowers1, Gaurav Malhotra1, Marin Dujmović1
1School of Psychological Science, University of Bristol, Bristol, UK j.bowers@bristol.ac.uk; https://jeffbowers.blogs.bristol.ac.uk/ gaurav.malhotra@bristol.ac.uk marin.dujmovic@bristol.ac.uk m.lleramontero@bristol.ac.uk christian.tsvetkov@bristol.ac.uk valerio.biscione@gmail.com.
The Behavioral and brain sciences
|December 6, 2023
概括
研究人员一致认为,心理学和深度神经网络 (DNN) 对人类视觉模型至关重要. 然而,关于模型的目的,评估和作的影响的辩论仍然存在,这导致了关于DNN与人类对应的潜在不合理的说法.
科学领域:
- 认知科学 认知科学
- 神经科学是一个神经科学.
- 计算机视觉 计算机视觉
背景情况:
- 心理学在开发人类视觉模型方面发挥着至关重要的作用.
- 深度神经网络 (DNN) 越来越多地被认为具有模拟人类视觉的潜力.
- 关于视觉研究中的计算模型的目的和评估存在分歧.
研究的目的:
- 为了解决计算视觉建模中的关键分歧.
- 批判性地评估深度神经网络 (DNN) - 人类对应的说法.
- 讨论营销作对认知科学中DNN模型解释的影响.
主要方法:
- 在计算视觉当前辩论的审查和综合.
- 对评估DNN与人类对应的方法进行批判性分析.
- 讨论替代建模方法的作用.
主要成果:
- 关于心理学和DNN对于视觉建模的重要性的协议.
- 确定与模型评估和目的有关的重大分歧.
- 由于作和方法问题,人们对不合理的索赔表示担忧.
结论:
- 虽然DNN是有前途的,但它们在人类视觉建模中的应用需要严格的评估.
- 不批判地接受DNN-人类对应的结果,可能会导致过分的结论.
- 需要进一步的研究来澄清DNN在理解认知中的作用和局限性.
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