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相关概念视频

Vision01:24

Vision

52.9K
Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
52.9K
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

537
Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
537
Visual System01:26

Visual System

498
Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...
498

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相关实验视频

Updated: May 31, 2025

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
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Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

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基于胡贝尔-维塞尔模型的立体定向识别的人工视觉系统.

Bin Li1, Yuki Todo2, Zheng Tang3,4

  • 1Division of Electrical Engineering and Computer Science, Kanazawa University, Kanazawa-shi 920-1192, Japan.

Biomimetics (Basel, Switzerland)
|January 24, 2025
PubMed
概括

这项研究引入了一个人工视觉系统 (AVS) 用于立体定向识别,灵感来自于Hubel-Wiesel模型. 该AVS有效地处理空间信息,实现高精度并增强用于3D对象识别的深度学习模型.

关键词:
胡贝尔 - 维塞尔模型人工视觉系统的人工视觉系统立体导向的选择性选择性

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Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues
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Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues

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Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition
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Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition

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相关实验视频

Last Updated: May 31, 2025

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

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Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues
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Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues

Published on: December 4, 2013

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Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition
07:45

Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition

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科学领域:

  • 神经科学是一个神经科学.
  • 计算机视觉 计算机视觉
  • 人工智能的人工智能

背景情况:

  • 立体导向选择性对于感知至关重要,但在较高的皮质区域不太了解.
  • 现有的模型缺乏用于高维空间信息处理的策略.
  • 胡贝尔-维塞尔模型启发了早期的视觉处理和计算机视觉算法.

研究的目的:

  • 为立体导向选择性提供概念和定量解释.
  • 开发一个人工视觉系统 (AVS) 用于立体定向识别.
  • 提高3D对象识别中的深度学习模型的性能和稳定性.

主要方法:

  • 模拟深度选择性细胞用于深度信息处理.
  • 开发了用于局部特征集成的简单立体导向选择性细胞.
  • 设计了复杂的立体导向选择性单元,用于全球特征集成,灵感来自于Hubel-Wiesel模型的局部到全球聚合.
  • 实现了一个人工视觉系统 (AVS) 用于立体定向识别.

主要成果:

  • 该AVS在立体声定向识别方面表现出有效性.
  • 在用于方向识别的噪音数据上获得了超过90%的准确性,优于深度模型.
  • 在3D对象识别任务中显著提高了深度模型的性能,稳定性和稳定性.
  • 增强了TransNeXt模型的准确性,从3D-MNIST上的73.1%到97.2%,以及3D-Fashion-MNIST上的56.1%到86.4%.

结论:

  • 拟议的模型提供了一种可靠,可解释和强大的方法来提取空间特征.
  • 为神经计算研究提供了简单的建模方法.
  • 该AVS框架促进了对立体导向选择性的理解和应用.