10 citations · 32 across the 13 of their papers we have counts for
5 papers · 1 filter
Efficient Generalization Improvement Guided by Random Weight Perturbation
Tao Li, Weihao Yan, Zehao Lei +4
To fully uncover the great potential of deep neural networks (DNNs), various learning algorithms have been developed to improve the model's generalization ability. Recently, sharpn…
Multi-head Ensemble of Smoothed Classifiers for Certified Robustness
Kun Fang, Qinghua Tao, Yingwen Wu +3
Randomized Smoothing (RS) is a promising technique for certified robustness, and recently in RS the ensemble of multiple Deep Neural Networks (DNNs) has shown state-of-the-art perf…
Online LiDAR-Camera Extrinsic Parameters Self-checking
Pengjin Wei, Guohang Yan, Yikang Li +3
With the development of neural networks and the increasing popularity of automatic driving, the calibration of the LiDAR and the camera has attracted more and more attention. This…
Unifying Gradients to Improve Real-world Robustness for Deep Networks
Yingwen Wu, Sizhe Chen, Kun Fang +1
The wide application of deep neural networks (DNNs) demands an increasing amount of attention to their real-world robustness, i.e., whether a DNN resists black-box adversarial atta…
CROON: Automatic Multi-LiDAR Calibration and Refinement Method in Road Scene
Pengjin Wei, Guohang Yan, Yikang Li +4
Sensor-based environmental perception is a crucial part of the autonomous driving system. In order to get an excellent perception of the surrounding environment, an intelligent sys…