Catfish density estimation by aerial images analysis and deep learning.

The food economic chain of many rivers is based on an important control of the presence of predatory fish in the water. The assessment of the predation pressure on migratory species cannot be done manually. Therefore some automatic techniques are needed. In this paper we propose, for the first time, a deep neural architecture to estimate the catfish density from Aerial Images taken on the Loire river. The proposed architecture is adapted to the problem in hand and some variations to existing approaches, never applied in this application context, are designed to better fit the needs of the problem. Preliminary results show the appropriateness of the proposal and form the foundations for future developments on this new application.