Class-specific discriminant regularization in real-time deep CNN models for binary classification problems

摘要

In this paper, we first propose lightweight deep CNN models, capable of effectively operating in real-time on-drone for high-resolution video input, addressing various binary classification problems, e.g. crowd, face, football player, and bicycle detection, in the context of media coverage of specific sport events by drones with increased decisional autonomy. Furthermore, we propose a novel class-specific discriminant regularizer in order to improve the generalization ability of the proposed real-time models, exploiting the nature of the considered two-class problems. The experimental evaluation on four datasets validates the effectiveness of the proposed regularizer in enhancing the generalization ability of the proposed models.