ImpactU Versión 3.11.2 Última actualización: Interfaz de Usuario: 16/10/2025 Base de Datos: 29/08/2025 Hecho en Colombia
Desarrollo e implementación de un método para la clasificación de imágenes alteradas, usando redes neuronales convolucionales y detección de ruido y bordes.
Today it is necessary the truth in the information at the moment of public or shares with others. Some ways to change the meaning of an image is with the use of any tool to change some pixels of the image, one way to know if an image has any forgery is with the use of computational intelligence and fake analysis areas. The proposed model consists in a preprocessing of the image to have the same size to implement gaussian noise estimation and sharpness detection. Finally, the sharpness and Gaussian noise is applied to the convolutional neural network to predict if the image has any forgery. The results of the convolutional neural network have a prediction of 89.54. With the detection of sharpness and noise is 90.54 of all of the images.
