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In this work, a deep learning approach has been developed to carry out road detection using only LIDAR data.
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X. Hu, F. S. A. Rodriguez, and A. Gepperth, “A multi-modal system for road detection and segmentation,” in 2014 IEEE Intelligent Vehicles Symposium Proceedings . IEEE, 2014, pp. 1365–1370
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R. Fernandes, C. Premebida, P. Peixoto, D. Wolf, and U. Nunes, “Road detection using high resolution lidar,” in 2014 IEEE Vehicle Power and Propulsion Conference (VPPC) , Oct 2014, pp. 1–6
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P. Y. Shinzato, D. F. Wolf, and C. Stiller, “Road terrain detection: Avoiding common obstacle detection assumptions using sensor fusion,” in 2014 IEEE Intelligent Vehicles Symposium Proceedings . IEEE, 2014, pp. 687–692
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Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature , vol. 521, no. 7553, pp. 436–444, 2015
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L. Xiao, B. Dai, D. Liu, T. Hu, and T. Wu, “Crf based road detection with multi-sensor fusion,” in Intelligent Vehicles Symposium (IV) , 2015
2015
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J. Tompson, R. Goroshin, A. Jain, Y. LeCun, and C. Bregler, “Efficient object localization using convolutional networks,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2015, pp. 648–656
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L. Ankit, K. Mehmet, S. Luis, and M. Hebert, “Map-supervised road detection,” in IEEE Intelligent Vehicles Symposium Proceedings , 2016
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2015
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2015
Cited alongside, same era.
J. Long, E. Shelhamer, and T. Darrell, “Fully convolutional networks for semantic segmentation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2015, pp. 3431–3440
2015
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2015
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2016
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2016
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G. L. Oliveira, W. Burgard, and T. Brox, “Efficient deep methods for monocular road segmentation.” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016) , 2016
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C. C. T. Mendes, V. Frémont, and D. F. Wolf, “Exploiting fully convolutional neural networks for fast road detection,” in 2016 IEEE International Conference on Robotics and Automation (ICRA) , May 2016, pp. 3174–3179
2016
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