ImpactU Versión 3.11.2 Última actualización: Interfaz de Usuario: 16/10/2025 Base de Datos: 29/08/2025 Hecho en Colombia
Una implementación computacional de un modelo de atención visual Bottom-up aplicado a escenas naturales A Computational Implementation of a Bottom-up Visual Attention Model Applied to Natural Scenes
The bottom-up visual attention model proposed by Itti et al. 2000 (1), has been a popular model since it exhibits certain neurobiological evidence of primates' vision. This work complements the computational model of this phenomenon using a neural network with realistic dynamics. This approximation is based on several topographical maps representing the objects saliency that construct a general representation (saliency map), which is the input for a dynamic neural network, whose local and global collaborative and competitive interactions converge to the main particularities (objects) presented by the visual scene as well.
