Discriminant Analysis Regularization in Lightweight Deep CNN Models
Maria Tzelepi, Anastasios Tefas · 2019
In this paper, we first propose lightweight deep CNN models, capable of effectively operating on-drone, in order to address various classification problems, i.e. crowd, football player, and bicycle detection, in the context of media coverage of specific sport events by drones with increased decisional autonomy. Subsequently, we propose a regularization technique, namely Discriminant Analysis regularization, aiming to enhance the generalization ability of the proposed models. The experimental evaluation validates the enhanced performance of the proposed regularizer.