Karl Tuvls

Fast Convergence for Object Detection by Learning how to Combine Error Functions

In this paper, we introduce an innovative method to improve the convergence speed and accuracy of object detection neural networks. Our approach, Converge-fast-auxnet, is based on employing multiple, dependent loss metrics and weighting them optimally using an on-line trained auxiliary network. Expe…