Image Recognition Applied to Security Systems: The Case of Burkina Faso

Abstract

In this article we propose à model composed of five layers of convolution and two layers of maxpooling and three layers of fully connected. What will allow image recognition to be applied to security systems: the case of Burkina Faso The main contributions are :-The establishment of a rapid and efficient aerial reconnaissance system ; -Stable and fluid navigation of drones by learning the identification of simulated targets -Improving security in Burkina Faso.The results show us that the accuracy of learning and testing increases with the number of epochs, this reflects that at each epoch the model learns more information. If the precision is decreased then we will need more information to make our model learn and therefore we must increase the number of epochs and vice versa. Similarly, the learning and validation error decreases with the number of epochs.