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

Color Vision

Color Vision

Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.

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,...

You might also read

Related Articles

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

Sort by

Same author

Unified biopolymer-based film design exploiting the multifunctional roles of tannic acid for beef preservation and real-time freshness monitoring.

Food research international (Ottawa, Ont.)·2026

Same author

Cohort profile: Sheyang Mini Birth Cohort Study (SMBCS).

BMJ open·2026

Same author

Structural characterization, rheological properties, and skin bioactivities of a glucomannan from Bletilla striata.

Natural products and bioprospecting·2026

Same author

Polysaccharide-protein composite systems in dysphagia-oriented food design: interactions, applications, and additive manufacturing.

Food chemistry·2026

Same author

Targeting the Skeletal Muscle Microenvironment: A Novel Therapeutic Strategy for Skeletal Muscle Aging.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology·2026

Same author

Prenatal exposure to metal(loid)s and hormone profile in umbilical cord serum: Evidence of sex-specific association.

Environmental research·2026

Search research articles

Related Experiment Video

Updated: Jul 2, 2025

Visualizing Visual Adaptation

Visualizing Visual Adaptation

Published on: April 24, 2017

Defense against adversarial attacks based on color space transformation.

Haoyu Wang¹, Chunhua Wu¹, Kangfeng Zheng¹

¹School of Cyberspace Security, Beijing University of Posts and Telecommunications, China.

Neural Networks : the Official Journal of the International Neural Network Society

|February 25, 2024

Summary

This study introduces a novel defense against adversarial attacks on deep learning models. By amplifying adversarial perturbations, the method makes attacks visible and invalidates them.

Keywords:

Adversarial attack Adversarial defense Deep learning Robustness

More Related Videos

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

Related Experiment Videos

Last Updated: Jul 2, 2025

Visualizing Visual Adaptation

Visualizing Visual Adaptation

Published on: April 24, 2017

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

Area of Science:

Computer Science
Artificial Intelligence
Machine Learning

Background:

Deep Learning (DL) models achieve high performance but are vulnerable to adversarial attacks.
Adversarial examples, subtle input perturbations, can cause misclassification.
Existing research suggests complete elimination of adversarial examples is not feasible.

Purpose of the Study:

To develop a defense method against adversarial attacks by invalidating existing examples and amplifying new ones.
To enhance the robustness of deep learning models against adversarial perturbations.
To make adversarial perturbations distinguishable to human observers.

Main Methods:

Invalidating existing adversarial examples by altering classification boundaries.
Increasing adversarial perturbations for newly generated examples to enhance visibility.
Implementing the defense strategy through color space transformation.

Main Results:

Demonstrated effectiveness and versatility of the proposed defense method on CIFAR-10, CIFAR-100, and Mini-ImageNet datasets.
Successfully rendered existing adversarial examples invalid.
Made adversarial perturbations more discernible to human perception.

Conclusions:

The proposed defense method, based on amplifying adversarial perturbations, is effective against adversarial attacks.
This represents a novel approach to adversarial defense in deep learning.
The method offers a practical solution for improving the robustness of AI systems.