Physically Realizable Adversarial Examples for LiDAR Object Detection

no code implementations • CVPR 2020 • James Tu, Mengye Ren, Siva Manivasagam, Ming Liang, Bin Yang, Richard Du, Frank Cheng, Raquel Urtasun

Modern autonomous driving systems rely heavily on deep learning models to process point cloud sensory data; meanwhile, deep models have been shown to be susceptible to adversarial attacks with visually imperceptible perturbations.

Adversarial Defense Autonomous Driving +4

3D-RADNet: Extracting labels from DICOM metadata for training general medical domain deep 3D convolution neural networks

no code implementations • MIDL 2019 • Richard Du, Varut Vardhanabhuti

We applied our method and extracted labels from a large amount of cancer imaging dataset from TCIA to train a medical domain 3D deep convolution neural network.

Liver Segmentation Transfer Learning