Please enter a description about the method here

**DropAttack** is an adversarial training method that adds intentionally worst-case adversarial perturbations to both the input and hidden layers in different dimensions and minimizes the adversarial risks generated by each layer.

DropAttack

DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks

RTMDet

Parametrized learnable activation function, based on the Padé approximant.

Year	2000
Data Source	CC BY-SA - https://paperswithcode.com

Viet-Anh on Software

What is: RTMDet: An Empirical Study of Designing Real-Time Object Detectors?

Viet-Anh on Software