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Deep learning models are extensively used in various safety critical applications.
Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Gal, Y. and Ghahramani, Z · 2016
Earlier work this paper cites.
Exploring spatial context for 3d semantic segmentation of point clouds
Engelmann, F., Kontogianni, T., Hermans, A., and Leibe, B · 2017
Earlier work this paper cites.
Simple and scalable predictive uncertainty estimation using deep ensembles
Lakshminarayanan, B., Pritzel, A., and Blundell, C · 2017
Earlier work this paper cites.
Segcloud: Semantic segmentation of 3d point clouds
Tchapmi, L., Choy, C., Armeni, I., Gwak, J., and Savarese, S · 2017
Cited alongside, same era.
Uncertainty estimation via stochastic batch normalization
Atanov, A., Ashukha, A., Molchanov, D., Neklyudov, K., and Vetrov, D · 2019
Cited alongside, same era.
Semantickitti: A dataset for semantic scene understanding of lidar sequences
Behley, J., Garbade, M., Milioto, A., Quenzel, J., Behnke, S., Stachniss, C., and Gall, J · 2019
Cited alongside, same era.
Nr20200319 tesla crash report, 2018a
NTSB
Cited in the paper.
Hwy18mh010 uber crash report, 2018b
NTSB
Cited in the paper.
Pointnet: Deep learning on point sets for 3d classification and segmentation
Qi, C. R., Su, H., Mo, K., and Guibas, L. J
Cited in the paper.
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Qi, C. R., Yi, L., Su, H., and Guibas, L. J
Cited in the paper.
3d graph neural networks for rgbd semantic segmentation
Qi, X., Liao, R., Jia, J., Fidler, S., and Urtasun, R
Cited in the paper.
Rangenet++: Fast and accurate lidar semantic segmentation
Milioto, A., Vizzo, I., Behley, J., and Stachniss, C · 2019
Later among the works it cites.
Dropconnect is effective in modeling uncertainty of bayesian deep networks
Mobiny, A., Nguyen, H. V., Moulik, S., Garg, N., and Wu, C. C · 2019
Later among the works it cites.
Squeezesegv2: Improved model structure and unsupervised domain adaptation for road-object segmentation from a lidar point cloud
Wu, B., Zhou, X., Zhao, S., Yue, X., and Keutzer, K · 2019
Later among the works it cites.
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