心理物理学可能是深度神经网络 (DNN) 模仿人类视觉的游戏改变者
Keerthi S Chandran1,2, Amrita Mukherjee Paul1,3, Avijit Paul4
1Center for Soft Computing Research, Indian Statistical Institute, Kolkata, India keerthischandran@gmail.com.
The Behavioral and brain sciences
|December 6, 2023
概括
心理上忠实的深度神经网络 (DNN) 可以使用心理物理数据来创建. 结合较小的DNN可以模拟复杂的大脑视觉,超越当前的单眼系统,模仿双眼人类视觉.
科学领域:
- 神经科学是一个神经科学.
- 计算机科学 计算机科学
- 人工智能的人工智能
背景情况:
- 目前的深度神经网络 (DNN) 主要使用单眼视觉,与人类大脑主要依赖双眼视觉不同.
- 开发心理忠实的DNN需要整合人类视觉感知数据.
研究的目的:
- 探索深度神经网络 (DNN) 的创建,这些深度神经网络准确地模拟人类心理视觉过程.
- 通过结合双眼视觉原则来研究增强DNN的方法.
- 通过模块化DNN提出模拟复杂生物视觉的框架.
主要方法:
- 使用心理物理数据训练深度神经网络 (DNN),以确保心理忠实.
- 为基本的视觉任务开发较小,专门的DNN.
- 结合这些专门的DNN来模拟更复杂的视觉活动.
主要成果:
- 证明了心理物理数据可以用来训练心理忠实DNN.
- 展示了组合模块化DNN以实现复杂的视觉处理的潜力.
- 与生物双眼视觉相比,强调了当前单眼DNN的局限性.
结论:
- 通过对心理物理数据的训练,可以实现心理忠实DNN.
- 一个模块化方法,结合专门的DNN,可以模拟先进的视觉认知.
- 未来的DNN开发应该考虑双眼视觉,以更好地模拟人类的能力.
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