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Language01:16

Language

908
Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
Corballis and Suddendorf (2007) and Tomasello and Rakoczy (2003) highlight the role of language in...
908
Components of Language01:24

Components of Language

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Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
815
Language Development01:22

Language Development

908
Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
908
Language and Cognition01:27

Language and Cognition

797
Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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pre-mRNA Processing02:01

pre-mRNA Processing

57.4K
In eukaryotic cells, transcripts made by RNA polymerase are modified and processed before exiting the nucleus. Unprocessed RNA is called precursor mRNA or pre-mRNA to distinguish it from mature mRNA.
Once about 20-40 ribonucleotides have been joined together by RNA polymerase, a group of enzymes adds a “cap” to the 5’ end of the growing transcript. In this process, a 5’ phosphate is replaced by modified guanosine that has a methyl group attached to it (7-Methyl...
57.4K
Velocity of an Object01:18

Velocity of an Object

199
Understanding how an object moves along a path requires distinguishing between motion over a time span and motion at a precise moment. A useful example is a vehicle traveling along a straight and level path, where its position at any given time is known. The initial step in analyzing this motion is to measure how far the vehicle travels over a fixed time period. This measurement, called average velocity, is computed by dividing the total change in position by the duration over which the change...
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Video Experimental Relacionado

Updated: Jan 30, 2026

Novel Object Recognition Test for the Investigation of Learning and Memory in Mice
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Novel Object Recognition Test for the Investigation of Learning and Memory in Mice

Published on: August 30, 2017

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Preentrenamiento contrastivo de lenguaje e imagen guiado por objetos para el reconocimiento de objetivos de tiro cero

Chenghao Zheng1

  • 1Southwest China Institute of Electronic Technology, Chengdu, 610036, Sichuan, China. zch.512@163.com.

Scientific reports
|January 28, 2026
PubMed
Resumen

Object-Guide CLIP (OG-CLIP) mejora los modelos visuales de lenguaje para la seguridad al mejorar el reconocimiento de objetivos. Logra una mayor precisión a través de grafos de conocimiento, procesamiento centrado en la región y características adaptativas, superando a los modelos estándar.

Palabras clave:
mecanismo de atenciónvisión por computadoraaprendizaje profundoreconocimiento de objetos

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Área de la Ciencia:

  • Ciencias de la Computación; Inteligencia Artificial; Aprendizaje Automático

Sus antecedentes:

  • Los modelos tradicionales de lenguaje visual (VLM) enfrentan limitaciones en datos semánticos, supresión de fondo y manejo de características multirresolución para aplicaciones de seguridad.
  • CLIP, un VLM prominente, presenta limitaciones en el reconocimiento de diversos objetivos debido a una semántica de datos de entrenamiento insuficiente y un procesamiento de características rígido.

Objetivo del estudio:

  • Presentar Object-Guide CLIP (OG-CLIP), un VLM avanzado diseñado para un reconocimiento de objetivos superior en sistemas de seguridad.
  • Superar las limitaciones de los VLM existentes integrando una nueva aumentación de datos, procesamiento centrado en el objetivo y representación adaptativa de características.

Principales métodos:

  • Aumentación de datos impulsada por grafos de conocimiento utilizando un grafo de conocimiento militar de 5000 categorías y un millón de pares de imágenes y texto.
  • Un módulo de Región de Interés (ROI) centrado en el objetivo que fusiona máscaras SAM 2 con características ViT para un enfoque mejorado y supresión de fondo.
  • Aprendizaje adaptativo multirresolución (MRL) con características continuas y ponderación dinámica de dimensiones para una granularidad flexible.

Principales resultados:

  • OG-CLIP logró un 84,28% de precisión media (mAcc) en 99 categorías de objetivos, superando a CLIP base en 11,36 puntos porcentuales.
  • Los estudios de ablación confirmaron la contribución significativa de cada componente propuesto al rendimiento general.
  • El modelo demostró un rendimiento superior en escenarios complejos, destacando su robustez.

Conclusiones:

  • OG-CLIP presenta un marco escalable y adaptable de modelado de visión y lenguaje para el reconocimiento de objetivos militares.
  • Las mejoras propuestas abordan eficazmente las limitaciones semánticas, el ruido de fondo y la inflexibilidad de las características en los VLM tradicionales.
  • Las direcciones futuras de investigación incluyen la expansión del conjunto de datos y la optimización del modelo para la eficiencia.