Jove
Visualize
Contáctanos
JoVE
x logofacebook logolinkedin logoyoutube logo
ACERCA DE JoVE
Visión GeneralLiderazgoBlogCentro de Ayuda JoVE
AUTORES
Proceso de PublicaciónConsejo EditorialAlcance y PolíticasRevisión por ParesPreguntas FrecuentesEnviar
BIBLIOTECARIOS
TestimoniosSuscripcionesAccesoRecursosConsejo Asesor de BibliotecasPreguntas Frecuentes
INVESTIGACIÓN
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchivo
EDUCACIÓN
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualCentro de Recursos para ProfesoresSitio de Profesores
Términos y Condiciones de Uso
Política de Privacidad
Políticas

Videos de Conceptos Relacionados

Coordination Number and Geometry02:57

Coordination Number and Geometry

19.0K
For transition metal complexes, the coordination number determines the geometry around the central metal ion. Table 1 compares coordination numbers to molecular geometry. The most common structures of the complexes in coordination compounds are octahedral, tetrahedral, and square planar.
19.0K
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

45.7K
VSEPR Theory for Determination of Electron Pair Geometries
45.7K
Convolution Properties II01:17

Convolution Properties II

583
The important convolution properties include width, area, differentiation, and integration properties.
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
The area property asserts that the area under the...
583
Geometry of Hyperbolas01:30

Geometry of Hyperbolas

492
A hyperbola consists of all points where the absolute difference of distances to two fixed points, called foci, remains constant. The standard equation isEach branch extends infinitely and approaches two asymptotes, which guide the curve’s behavior. The parameters a and b define key features: a measures the distance from the center to each vertex along the transverse axis, while b influences the slopes of the asymptotes. The asymptotes have equationsA rectangle centered at the origin with...
492
Subliminal Perception01:15

Subliminal Perception

782
Subliminal perception refers to the processing of sensory information that occurs below the level of conscious awareness. Researchers study subliminal perception by presenting a stimulus, such as a word or image, very quickly, typically around 50 milliseconds. This rapid presentation is often followed by another stimulus, such as a pattern of dots or lines, which blocks further mental processing of the initial stimulus. As a result, if participants cannot identify the initial stimulus better...
782
Factors Affecting Perception01:25

Factors Affecting Perception

2.7K
Perception is influenced by perceptual set, context, motivation, and emotion. Perceptual set, or perceptual expectancy, refers to the tendency to perceive things in a particular way, influenced by previous experiences and expectations. This phenomenon affects the interpretation of stimuli, creating a set of mental tendencies and assumptions that impact sensory perceptions of sound, taste, touch, and sight.
An illustrative example of a perceptual set is the scenario where an airline pilot told...
2.7K

También podría leer

Artículos Relacionados

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

Ordenar por
Same author

U-ResNet, a Novel Network Fusion Method for Image Classification and Segmentation.

Sensors (Basel, Switzerland)·2025
Same author

mTORC1 signaling requires proteasomal function and the involvement of CUL4-DDB1 ubiquitin E3 ligase.

Cell cycle (Georgetown, Tex.)·2008
Same author

Prospective study of liver transplant recipients with HCV infection: evidence for a causal relationship between HCV and insulin resistance.

Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society·2008
Same author

Quantitative gel electrophoresis: sources of variation.

Journal of proteome research·2008
Same author

Evidence that the Nijmegen breakage syndrome protein, an early sensor of double-strand DNA breaks (DSB), is involved in HIV-1 post-integration repair by recruiting the ataxia telangiectasia-mutated kinase in a process similar to, but distinct from, cellular DSB repair.

Virology journal·2008
Same author

Bioactive polybrominated diphenyl ethers from the marine sponge Dysidea sp.

Journal of natural products·2008
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
Ver todos los artículos relacionados

Video Experimental Relacionado

Updated: Jan 29, 2026

Topographical Estimation of Visual Population Receptive Fields by fMRI
06:02

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

9.7K

Pose-Perceptive Convolution: Aprendizaje de Campos Receptivos Adaptativos a la Geometría para una Estimación Robusta

Yi Lai1, Yaqing Song1, Qixian Zhang2

  • 1College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 201418, China.

Sensors (Basel, Switzerland)
|January 28, 2026
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio presenta Pose-Perceptive Convolution (PPC) para abordar las desalineaciones geométricas en la estimación de la pose 6D de objetos. PPF-Net, que utiliza PPC, mejora significativamente la precisión con un costo computacional mínimo.

Palabras clave:
estimación de pose 6Dfusión RGB-profundidaddesalineación geométricaadaptación del campo receptivo

Más Videos Relacionados

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

2.2K
Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

12.2K

Videos de Experimentos Relacionados

Last Updated: Jan 29, 2026

Topographical Estimation of Visual Population Receptive Fields by fMRI
06:02

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

9.7K
Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

2.2K
Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

12.2K

Área de la Ciencia:

  • Visión por Computadora
  • Robótica
  • Aprendizaje Automático

Sus antecedentes:

  • La estimación de la pose 6D de objetos es vital para la robótica y la RA, pero se ve desafiada por las relaciones de aspecto y las variaciones de apariencia de los objetos.
  • Los métodos existentes a menudo pasan por alto las desalineaciones geométricas entre los campos receptivos convolucionales fijos y las morfologías de los objetos.
  • Esta desalineación limita el rendimiento de las técnicas actuales de estimación de pose 6D.

Objetivo del estudio:

  • Proponer una novedosa convolución perceptiva de la pose (PPC) para resolver desalineaciones geométricas en la extracción de características.
  • Introducir una nueva red de fusión perceptiva de la pose (PPF-Net) para una estimación robusta de la pose 6D de objetos.
  • Demostrar una estrategia eficiente de extracción de características frontales para mejorar la precisión de la estimación de la pose.

Principales métodos:

  • Desarrolló la convolución perceptiva de la pose (PPC) que adapta dinámicamente la forma y la densidad de muestreo del campo receptivo.
  • Construyó una red de fusión perceptiva de la pose (PPF-Net) que integra PPC para la extracción de características.
  • Evaluó PPF-Net en cuatro conjuntos de datos de referencia, incluidos MP6D y YCB-Video.

Principales resultados:

  • PPF-Net logró una mejora del 19,4% en la puntuación VSD sobre FFB6D en MP6D.
  • Alcanzó una precisión ADD-S del 96,7% en YCB-Video, acercándose al estado del arte.
  • Demostró ganancias significativas de precisión con una sobrecarga computacional mínima.

Conclusiones:

  • La convolución perceptiva de la pose resuelve eficazmente las desalineaciones geométricas en la estimación de la pose 6D de objetos.
  • PPF-Net ofrece una solución robusta y computacionalmente eficiente para una estimación precisa de la pose 6D.
  • La extracción de características frontales es una estrategia eficiente para mejorar la robustez de la estimación de la pose 6D.