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2018 Journal Articles [20]

An Extended Filtered Channel Framework for Pedestrian Detection

You, M., Zhang, Y., Shen, C., & Zhang, X. (2018). An Extended Filtered Channel Framework for Pedestrian Detection. IEEE Transactions on Intelligent Transportation Systems, 19(5), 1640–1651. https://doi.org/10.1109/TITS.2018.2807199

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An Embarrassingly Simple Approach to Visual Domain Adaptation

Lu, H., Shen, C., Cao, Z., Xiao, Y., & van den Hengel, A. (2018). An Embarrassingly Simple Approach to Visual Domain Adaptation. IEEE Transactions on Image Processing, 27(7), 3403–3417. https://doi.org/10.1109/TIP.2018.2819503

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Cluster Sparsity Field: An Internal Hyperspectral Imagery Prior for Reconstruction

Zhang, L., Wei, W., Zhang, Y., Shen, C., van den Hengel, A., & Shi, Q. (2018). Cluster Sparsity Field: An Internal Hyperspectral Imagery Prior for Reconstruction. International Journal of Computer Vision, 126(8), 797–821. https://doi.org/10.1007/s11263-018-1080-8

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Multi-label learning based deep transfer neural network for facial attribute classification

Zhuang, N., Yan, Y., Chen, S., Wang, H., & Shen, C. (2018). Multi-label learning based deep transfer neural network for facial attribute classification. Pattern Recognition, 80, 225–240. https://doi.org/10.1016/J.PATCOG.2018.03.018

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Multi-Task Structure-aware Context Modeling for Robust Keypoint-based Object Tracking

Li, X., Zhao, L., Ji, W., Wu, Y., Wu, F., Yang, M.-H., Dacheng, T., Reid, I. (2018). Multi-Task Structure-aware Context Modeling for Robust Keypoint-based Object Tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1–1. https://doi.org/10.1109/TPAMI.2018.2818132 *In Press

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The limits and potentials of deep learning for robotics

Sünderhauf, N., Brock, O., Scheirer, W., Hadsell, R., Fox, D., Leitner, J., Upcroft, B., Abbeel, P., Burgard, W., Milford, M., & Corke, P. (2018). The limits and potentials of deep learning for robotics. The International Journal of Robotics Research, 37(4–5), 405–420. http://doi.org/10.1177/0278364918770733

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Automating analysis of vegetation with computer vision: Cover estimates and classification

McCool, C., Beattie, J., Milford, M., Bakker, J. D., Moore, J. L., & Firn, J. (2018). Automating analysis of vegetation with computer vision: Cover estimates and classification. Ecology and Evolution, 8(12), 6005–6015. http://doi.org/10.1002/ece3.4135

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A rapidly deployable classification system using visual data for the application of precision weed management

Hall, D., Dayoub, F., Perez, T., & McCool, C. (2018). A rapidly deployable classification system using visual data for the application of precision weed management. Computers and Electronics in Agriculture, 148, 107–120. http://doi.org/10.1016/J.COMPAG.2018.02.023

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Measures of incentives and confidence in using a social robot

Robinson, N. L., Connolly, J., Johnson, G. M., Kim, Y., Hides, L., & Kavanagh, D. J. (2018). Measures of incentives and confidence in using a social robot. Science Robotics, 3(21), eaat6963. http://doi.org/10.1126/scirobotics.aat6963

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Glare-free retinal imaging using a portable light field fundus camera

Palmer, D. W., Coppin, T., Rana, K., Dansereau, D. G., Suheimat, M., Maynard, M. Atchison, D. A., Roberts, J., Crawford, R., & Jaiprakash, A. (2018). Glare-free retinal imaging using a portable light field fundus camera. Biomedical Optics Express, 9(7), 3178. http://doi.org/10.1364/BOE.9.003178

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Learning to Detect Aircraft for Long-Range Vision-Based Sense-and-Avoid Systems

James, J., Ford, J. J., & Molloy, T. L. (2018). Learning to Detect Aircraft for Long-Range Vision-Based Sense-and-Avoid Systems. IEEE Robotics and Automation Letters, 3(4), 4383–4390. http://doi.org/10.1109/LRA.2018.2867237

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Multimodal Trip Hazard Affordance Detection on Construction Sites

McMahon, S., Sunderhauf, N., Upcroft, B., & Milford, M. (2018). Multimodal Trip Hazard Affordance Detection on Construction Sites. IEEE Robotics and Automation Letters, 3(1), 1–8. http://doi.org/10.1109/LRA.2017.2719763

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Leveraging variable sensor spatial acuity with a homogeneous, multi-scale place recognition framework

Jacobson, A., Chen, Z., & Milford, M. (2018). Leveraging variable sensor spatial acuity with a homogeneous, multi-scale place recognition framework. Biological Cybernetics, 1–17. http://doi.org/10.1007/s00422-017-0745-7

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Rhythmic Representations: Learning Periodic Patterns for Scalable Place Recognition at a Sublinear Storage Cost

Yu, L., Jacobson, A., & Milford, M. (2018). Rhythmic Representations: Learning Periodic Patterns for Scalable Place Recognition at a Sublinear Storage Cost. IEEE Robotics and Automation Letters, 3(2), 811–818. http://doi.org/10.1109/LRA.2018.2792144

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Output regulation for systems on matrix Lie-groups

de Marco, S., Marconi, L., Mahony, R., & Hamel, T. (2018). Output regulation for systems on matrix Lie-groups. Automatica, 87, 8–16. https://doi.org/10.1016/J.AUTOMATICA.2017.08.006

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Leveraging variable sensor spatial acuity with a homogeneous, multi-scale place recognition framework

Jacobson, A., Chen, Z., & Milford, M. (2018). Leveraging variable sensor spatial acuity with a homogeneous, multi-scale place recognition framework. Biological Cybernetics, 1–17. http://doi.org/10.1007/s00422-017-0745-7

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Rhythmic Representations: Learning Periodic Patterns for Scalable Place Recognition at a Sublinear Storage Cost.

Yu, L., Jacobson, A., & Milford, M. (2018). Rhythmic Representations: Learning Periodic Patterns for Scalable Place Recognition at a Sublinear Storage Cost. IEEE Robotics and Automation Letters, 3(2), 811–818. http://doi.org/10.1109/LRA.2018.2792144

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Multimodal Trip Hazard Affordance Detection on Construction Sites

McMahon, S., Sunderhauf, N., Upcroft, B., & Milford, M. (2018). Multimodal Trip Hazard Affordance Detection on Construction Sites. IEEE Robotics and Automation Letters, 3(1), 1–8. http://doi.org/10.1109/LRA.2017.2719763

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Special issue on deep learning in robotics

Sünderhauf, N., Leitner, J., Upcroft, B., & Roy, N. (2018, April 27). Special issue on deep learning in robotics. The International Journal of Robotics Research. SAGE PublicationsSage UK: London, England. http://doi.org/10.1177/0278364918769189

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Multi-Modal Trip Hazard Affordance Detection On Construction Sites

McMahon, S., Sunderhauf, N., Upcroft, B., & Milford, M. (2018). Multimodal Trip Hazard Affordance Detection on Construction Sites. IEEE Robotics and Automation Letters, 3(1), 1–8. http://doi.org/10.1109/LRA.2017.2719763

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