Search research articles

ACERCA DE JoVE

Visión General Liderazgo Blog Centro de Ayuda JoVE

AUTORES

Proceso de Publicación Consejo Editorial Alcance y Políticas Revisión por Pares Preguntas Frecuentes Enviar

BIBLIOTECARIOS

Testimonios Suscripciones Acceso Recursos Consejo Asesor de Bibliotecas Preguntas Frecuentes

INVESTIGACIÓN

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archivo

EDUCACIÓN

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Centro de Recursos para Profesores Sitio de Profesores

Términos y Condiciones de Uso

Política de Privacidad

Videos de Conceptos Relacionados

Corrosion

Corrosion

The degradation of metals due to natural electrochemical processes is known as corrosion. Rust formation on iron, tarnishing of silver, and the blue-green patina that develops on copper are examples of corrosion. Corrosion involves the oxidation of metals. Sometimes it is protective, such as the oxidation of copper or aluminum, wherein a protective layer of metal oxide or its derivatives forms on the surface, protecting the underlying metal from further oxidation. In other cases, corrosion is...

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.

Corrosion of Reinforcement

Corrosion of Reinforcement

The corrosion of steel reinforcement within concrete is a process influenced by the material's inherent properties and external factors. The high pH level of around 13, provided by calcium hydroxide present in concrete, initially protects the steel reinforcement by promoting the formation of a passive iron oxide layer on its surface.
However, over time and under certain conditions like carbonation, chloride ingress, and cracking this protective state can be compromised. Steel has areas with...

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.

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.

COPD: Pathogenesis and Clinical Features

COPD: Pathogenesis and Clinical Features

Chronic obstructive pulmonary disease (COPD) is a group of lung conditions that progressively worsen over time, including chronic bronchitis and emphysema. This cluster of diseases collectively leads to a gradual and irreversible decline in lung function over time.
The primary cause for the onset of COPD is cigarette smoking and exposure to air pollution. These hazardous factors initiate a chain reaction within the lungs, resulting in chronic inflammation, damage to the airways, and a...

También podría leer

Artículos Relacionados

Artículos vinculados a este trabajo por autores compartidos, revista y gráfico de citas.

Ordenar por

Same author

Gold wrist-assisted PFNA reduces internal complications and enhances recovery in obese osteoporotic patients with intertrochanteric femur fractures.

PloS one·2026

Same author

A critical role for mitochondrial dynamics in cigarette smoke condensate-induced RPE senescence.

Free radical biology & medicine·2026

Same author

Ontogenetic Shifts in Mycorrhiza-Mediated Neighborhood Effects Among Multi-Stemmed Species in a Subtropical Forest.

Plants (Basel, Switzerland)·2026

Same author

Ultrasound-Assisted Soaking Facilitates Purine Dissolution from Soybean Powder: Development and Preliminary Application of Low-Purine Soybean Powder.

Foods (Basel, Switzerland)·2026

Same author

Red Monascus pigments attenuate fructose-driven bovine serum albumin (BSA) glycation via non-covalent and covalent interactions with proteins.

Food chemistry·2026

Same author

A Biomimetic Nanozyme Engineered via Coordination and Confinement for Photothermal-Reinforced Catalytic Detection of Extracellular Vesicles and Diagnosis of Cancer.

Analytical chemistry·2026

Search research articles

Video Experimental Relacionado

Updated: Jan 29, 2026

Metal Corrosion and the Efficiency of Corrosion Inhibitors in Less Conductive Media

Metal Corrosion and the Efficiency of Corrosion Inhibitors in Less Conductive Media

Published on: November 3, 2018

Detección y Extracción de Características de Corrosión de Pernos de Roca Basada en Visión por Computadora

Shucan Lu¹, Saisai Wu¹, Xinxin Ma¹

¹Shaanxi Key Laboratory of Geotechnical and Underground Space Engineering, School of Resources Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China.

Materials (Basel, Switzerland)

|January 28, 2026

Resumen

Este estudio presenta un método automatizado para la detección de corrosión de pernos de roca utilizando procesamiento de imágenes y aprendizaje profundo. La técnica cuantifica con precisión la corrosión, mejorando las estrategias de seguridad estructural y mantenimiento.

Palabras clave:

visión por computadora detección de corrosión aprendizaje profundo dimensión fractal procesamiento de imágenes

Más Videos Relacionados

Potentiodynamic Corrosion Testing

Potentiodynamic Corrosion Testing

Published on: September 4, 2016

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

Videos de Experimentos Relacionados

Last Updated: Jan 29, 2026

Metal Corrosion and the Efficiency of Corrosion Inhibitors in Less Conductive Media

Metal Corrosion and the Efficiency of Corrosion Inhibitors in Less Conductive Media

Published on: November 3, 2018

Potentiodynamic Corrosion Testing

Potentiodynamic Corrosion Testing

Published on: September 4, 2016

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

Área de la Ciencia:

Ingeniería
Ciencia de Materiales
Ciencias de la Computación

Sus antecedentes:

La corrosión de los pernos de roca representa riesgos significativos para la seguridad de la ingeniería y la longevidad de la infraestructura.
El monitoreo y mantenimiento efectivos son cruciales para mitigar estos riesgos.

Objetivo del estudio:

Desarrollar un enfoque integrado para la detección automática de corrosión de pernos de roca.
Mejorar la precisión y confiabilidad de la evaluación de la corrosión utilizando métodos computacionales avanzados.

Principales métodos:

Se utilizaron algoritmos de detección de objetos de visión por computadora con una Red de Pirámide de Características para una detección mejorada a escala múltiple.
Se empleó binarización de imágenes y análisis de matrices en escala de grises para la extracción de características.
Se aplicó modelado de Movimiento Browniano Fraccional para la simulación de morfología de corrosión y el cálculo de características fractales.

Principales resultados:

El modelo automatizado identificó y cuantificó con precisión las características de corrosión, incluida la densidad de picaduras.
La dimensión fractal aumentó significativamente con el tiempo de corrosión, sirviendo como un indicador confiable de la rugosidad de la superficie y la tasa de corrosión.
El estudio validó la precisión de los cálculos de características fractales a través de la simulación de morfología.

Conclusiones:

El marco integrado que combina procesamiento de imágenes, aprendizaje profundo y teoría fractal proporciona una solución robusta para el monitoreo de la corrosión de pernos de roca.
Este enfoque ofrece un método cuantitativo confiable para evaluar la corrosión de metales, mejorando las estrategias de mantenimiento y garantizando la seguridad de la ingeniería.