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IA Generativa con Imágenes

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IA Generativa con Imágenes

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Explora IA generativa con imágenes

Created by

ANAHI CAROLINA BAJANA ROCHINA
ANAHI CAROLINA BAJANA ROCHINA
Ecuador

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IA Generativa con Imágenes
 

IA Generativa con ImágenesOnline version

Explora IA generativa con imágenes

by ANAHI CAROLINA BAJANA ROCHINA
1

¿Qué técnica genera imágenes a partir de ruido y un prompt?

2

¿Qué modelo usa redes para crear imágenes realistas a partir de ruido?

3

¿Qué es un prompt en IA generativa de imágenes?

4

Ventaja de la difusión sobre GAN?

5

Riesgo ético clave de IA generativa de imágenes?

6

Qué práctica facilita verificar si una imagen es real?

7

Qué es el overfitting en IA generativa de imágenes?

8

Qué mide la resolución de una imagen generada?

9

Qué práctica reduce sesgos en imágenes generadas?

10

¿Qué es un 'diffusion model'?

Explicación

La difusión itera para obtener detalles a partir de ruido según el prompt.

Los GAN usan una red generadora y otra discriminadora para aprender.

El prompt dirige qué y cómo generar la imagen.

Las diffusion models suelen ser más estables y diversas.

Puede generar imágenes engañosas; requiere responsabilidad.

Huellas o marcas ayudan a identificar generación artificial.

El modelo repite imágenes de entrenamiento si está sobreajustado.

La resolución indica cuántos píxeles contiene la imagen.

Datos diversos minimizan sesgos en resultados.

Genera imágenes desde ruido evolucionando en pasos sucesivos.

 
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