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Un sistema de visión neuromórfica bajo demanda habilitado por un dispositivo neuromórfico de múltiples paradigmas y
Biyi Jiang1, Jiayi Xu1, Liang Ran2
1School of Microelectronics, Southern University of Science and Technology, Shenzhen, China.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|February 11, 2026
Resumen
Este estudio presenta un sistema de visión inteligente ultra-reconfigurable, que cierra la brecha entre la flexibilidad y la eficiencia energética. El nuevo sistema logra un rendimiento superior para escenarios dinámicos y estáticos, superando las tecnologías actuales.
Área de la Ciencia:
- La ingeniería neuromórfica es una ingeniería neuromórfica.
- Visión por ordenador Visión por ordenador Visión por ordenador Visión por ordenador Visión por ordenador
- Ciencia de los materiales Ciencia de los materiales.
Sus antecedentes:
- Los actuales sistemas de visión inteligente carecen de la flexibilidad y eficiencia energética necesarias para escenarios dinámicos.
- Los sistemas existentes se basan en arquitecturas rígidas y dispositivos de función limitada, lo que dificulta la adaptabilidad.
- Los sistemas de visión biológica ofrecen un punto de referencia para una alta inteligencia, eficiencia y flexibilidad.
Objetivo del estudio:
- Desarrollar un sistema de visión inteligente ultra reconfigurable bajo demanda.
- Para cerrar la brecha neuromórfica permitiendo la conmutación perfecta entre las funcionalidades.
- Para lograr simultáneamente una alta inteligencia, eficiencia y flexibilidad en los sistemas de visión.
Principales métodos:
- Desarrolló una matriz de dispositivos multi-paradigma capaz de cambiar entre los modos de picado, no picado, imágenes neuromórficas (NI) e inteligencia artificial (IA).
- Implementó un diseño de circuito y arquitectura reconfigurable para la asignación de recursos bajo demanda.
- Se ha demostrado una verdadera reconfigurabilidad a nivel de dispositivo, célula, matriz y sistema.
Principales resultados:
- Se han logrado eficiencias energéticas superiores de hasta 52,6 TOPS/W (NI-centric) y 75,5 TOPS/W (NI/AI híbrido).
- Demostración de la asignación de recursos bajo demanda entre las funcionalidades de NI y AI para imágenes y reconocimiento inteligentes.
- Se habilitaron transiciones sin fisuras entre los modos de picado (dinámico) y no picado (estático).
Conclusiones:
- El sistema desarrollado ofrece una reconfigurabilidad y eficiencia energética sin precedentes para la visión inteligente.
- Este trabajo representa un avance significativo hacia la imitación de las capacidades del sistema de visión biológica.
- El sistema proporciona una solución flexible y eficiente para tareas de procesamiento visual dinámicas e impredecibles.
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