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Visual System01:26

Visual System

2.1K
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...
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Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

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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.
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Vision01:24

Vision

60.8K
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.
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Natural and Artificial Concepts01:24

Natural and Artificial Concepts

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In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
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Photoreceptors and Visual Pathways01:22

Photoreceptors and Visual Pathways

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At the molecular level, visual signals trigger transformations in photopigment molecules, resulting in changes in the photoreceptor cell's membrane potential. The photon's energy level is denoted by its wavelength, with each specific wavelength of visible light associated with a distinct color. The spectral range of visible light, classified as electromagnetic radiation, spans from 380 to 720 nm. Electromagnetic radiation wavelengths exceeding 720 nm fall under the infrared category,...
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Tactile and Chemical Senses01:27

Tactile and Chemical Senses

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Tactile senses encompass touch, temperature, and pain, each mediated by specific receptors. Touch receptors detect mechanical energy or pressure against the skin. Sensory fibers from these receptors enter the spinal cord and relay information to the brain stem. Here, most fibers cross over to the opposite side of the brain. The touch information then moves to the thalamus, which projects a map of the body's surface onto the somatosensory areas of the parietal lobes in the cerebral cortex.
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Related Experiment Video

Updated: Mar 1, 2026

Using High Resolution Computed Tomography to Visualize the Three Dimensional Structure and Function of Plant Vasculature
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Using High Resolution Computed Tomography to Visualize the Three Dimensional Structure and Function of Plant Vasculature

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Natural Inspired Intelligent Visual Computing and Its Application to Viticulture.

Li Minn Ang1,2, Kah Phooi Seng3,4,5, Feng Lu Ge6

  • 1School of Computing & Mathematics, Charles Sturt University, Wagga Wagga 2678, Australia. lang@csu.edu.au.

Sensors (Basel, Switzerland)
|May 27, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces artificial immune system (AIS) algorithms for grape berry detection in viticulture. The developed AIS approach significantly outperforms traditional methods in identifying grape berries from vineyard images.

Keywords:
artificial immune systemintelligent systemnatural inspired computingvisual information processingviticulture applications

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Agricultural Technology

Background:

  • Viticulture relies on accurate grape berry detection for yield estimation and quality assessment.
  • Traditional image processing methods often struggle with natural variations in vineyard conditions.
  • Intelligent computing offers potential for enhanced visual information processing in agriculture.

Purpose of the Study:

  • To review visual information processing applications in viticulture.
  • To develop novel natural-inspired computing algorithms using artificial immune system (AIS) techniques for grape berry detection.
  • To apply and evaluate these algorithms on real-world vineyard images.

Main Methods:

  • Developed AIS algorithms based on the clonal selection algorithm (CSA).
  • Utilized a fitness model for precise arc detection in grape berry images.
  • Extended arc detection to multiple arcs and ring detectors for comprehensive berry identification.
  • Compared performance against Circular Hough Transform (CHT) and a parameter-free circle detection technique (RPCD).

Main Results:

  • The proposed AIS approach achieved a significantly higher F-score of 0.71.
  • Traditional methods, CHT and RPCD, yielded much lower F-scores of 0.28 and 0.30, respectively.
  • Demonstrated the effectiveness of AIS in detecting grape berries under natural vineyard conditions.

Conclusions:

  • Artificial immune system (AIS) algorithms offer a superior method for grape berry detection compared to conventional techniques.
  • The developed CSA-based approach shows strong potential for real-world viticulture applications.
  • Intelligent computing, specifically AIS, enhances visual information processing for precision agriculture.