Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Vision

Vision

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.

Depth Perception and Spatial Vision

Depth Perception and Spatial Vision

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.

Introduction to Learning

Introduction to Learning

Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...

Accessory Structures of the Eye

Accessory Structures of the Eye

Optical perception, or vision, is an extraordinary sense dependent on converting light signals received via the ocular organs. These organs, known as eyes, are securely positioned within the bony cavities of the skull, called orbits. The orbits serve a dual purpose: a protective shield for the ocular globes and a stable attachment point for the soft ocular tissues. The eye's external protective mechanisms include the eyelids, which are edged with lashes that act as a barrier against foreign...

Photoreceptors and Visual Pathways

Photoreceptors and Visual Pathways

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, whereas...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Assessment of cerebral hemodynamics in patients with acute brain injury: a group-based multivariate trajectory approach.

Frontiers in neurology·2026

Same author

Integrative PANoptosis-focused omics analysis uncovers GSDMC as a candidate biomarker in breast cancer.

Frontiers in cell and developmental biology·2026

Same author

Histone lactylation at H4K12 promotes macrophage-fibroblast crosstalk in neodymium oxide-induced pulmonary fibrosis via the PIK3R2/PI3K/Akt/mTOR axis.

Chemico-biological interactions·2026

Same author

Robust uranium-capturing membranes enabled by synergistic sulfonation and thiol-ene click crosslinking.

Water research·2026

Same author

Insights into developmental impairment, oxidative stress, and immune-metabolic dysregulation induced by lead exposure in honeybee larvae (Apis mellifera).

Ecotoxicology and environmental safety·2026

Same author

Electronic Delocalization-Confinement Coupling in Edge-Coordinated CQDs@MXene Enables Hydrogen-Bond Modulation for Ultrafast Proton Transport.

Advanced materials (Deerfield Beach, Fla.)·2026

Search research articles

Related Experiment Videos

Introduction to the First Workshop on Vision Foundation Models and Generative AI for Accessibility.

Yapeng Tian¹, Yuhang Zhao², Jon E Froehlich³

¹University of Texas at Dallas, Richardson, TX, USA.

... IEEE International Conference on Computer Vision Workshops. IEEE International Conference on Computer Vision

|July 16, 2026

Summary

Foundation models and generative AI offer powerful tools for accessibility, but present challenges like bias and data scarcity. This workshop fosters collaboration to develop responsible AI for assistive technologies.

Related Experiment Videos

Area of Science:

Artificial Intelligence
Computer Vision
Human-Computer Interaction
Accessibility Research

Background:

Recent advances in vision foundation models and generative AI enable new applications.
These AI technologies hold significant potential for developing assistive technologies.
Applying AI in accessibility contexts faces challenges such as bias and data limitations.

Purpose of the Study:

To identify challenges in applying AI to accessibility.
To explore emerging opportunities for AI in assistive technologies.
To foster collaboration among researchers in AI and accessibility.

Main Methods:

Workshop bringing together experts from computer vision, HCI, and accessibility.
Discussion and identification of key challenges and opportunities.
Focus on building inclusive and responsible AI systems.

Main Results:

Identified key challenges: fairness, bias, data scarcity, interpretability, and deployment.
Explored emerging opportunities for AI-powered assistive technologies.
Highlighted the need for interdisciplinary collaboration.

Conclusions:

AI foundation models and generative AI can significantly enhance accessibility.
Addressing challenges like bias and data scarcity is crucial for responsible development.
Collaboration is essential for creating effective and inclusive AI-driven accessibility solutions.