In this paper, a novel Deep Neural Network topology is presented with the objective of recognizing the Aedes aegypti and Aedes albopictus mosquito in their larvarian stage, which are the vectors that cause Dengue, Chikungunya, Zika and Yellow Fever outbreaks. This solution allows to determine if a sample image is a larva of the Aedes aegypti or Aedes albopictus mosquito with an accuracy of 91.28%, a true positive rate of 94.18% and a true negative rate of 88.37%. This Deep Neural Network topology allows the implementation of fast and accurate preventive measures in under-developed countries and isolated areas where a trained specialist might not be available.