Multimodal Vision Research Laboratory

MVRL

research area: LiDAR Processing

See below for a list of our publications in this area. You can see an unfiltered list of our publications or lists filtered for the following research areas: agriculture; astronomical imagery and data; camera calibration; biodiversity and conservation; generative modeling; LiDAR Processing; image localization; medical and biological imaging; image motion; remote sensing and mapping; social media; video surveillance and object tracking; timelapse imaging; transportation; and outdoor webcam imagery.

publications

  1. Rafique MU, Zhu J, Jacobs N. 2021. Automatic Segmentation of Sinkholes Using a Convolutional Neural Network. Earth and Space Science:19. DOI: 10.1002/essoar.10509794.1.
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  2. Jones D, Jacobs N. 2021. Intensity Harmonization for Airborne LiDAR. In: IEEE International Geoscience and Remote Sensing Symposium (IGARSS). DOI: 10.1109/IGARSS47720.2021.9553605.
    bibtex | paper | doi
  3. Chen M, Hadzic A, Song W, Jacobs N. 2021. Applications of Deep Machine Learning to Highway Safety and Usage Assessment. In: Transportation Research Board Workshop (Sponsored by AED50).
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  4. Zhu J, Nolte A, Jacobs N, Ye M. 2020. Machine Learning in Identifying Karst Sinkholes from LiDAR-Derived Topographic Depressions in the Bluegrass Region of Kentucky. Journal of Hydrology. DOI: 10.1016/j.jhydrol.2020.125049.
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  5. Blanton H, Grate S, Jacobs N. 2020. Surface Modeling for Airborne LiDAR. In: IEEE International Geoscience and Remote Sensing Symposium (IGARSS). DOI: 10.1109/IGARSS39084.2020.9323522.
    bibtex | paper | doi | tweet
  6. Hadzic A, Blanton H, Song W, Chen M, Workman S, Jacobs N. 2020. RasterNet: Modeling Free-Flow Speed using LiDAR and Overhead Imagery. In: IEEE/ISPRS Workshop: Large Scale Computer Vision for Remote Sensing (EARTHVISION). DOI: 10.1109/CVPRW50498.2020.00112.
    bibtex | paper | website | doi | tweet
  7. a thumbnail for Deep Learning for Conifer/Deciduous Classification of Airborne LiDAR 3D Point Clouds Representing Individual Trees
    Hamraz H, Jacobs NB, Contreras MA, Clark CH. 2019. Deep Learning for Conifer/Deciduous Classification of Airborne LiDAR 3D Point Clouds Representing Individual Trees. ISPRS Journal of Photogrammetry and Remote Sensing 158:219–230. DOI: 10.1016/j.isprsjprs.2019.10.011.
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  8. Zhang Y, Liang G, Salem T, Jacobs N. 2019. Defense-PointNet: Protecting PointNet Against Adversarial Attacks. In: The Next Frontier of Big Data From LiDAR Workshop (co-located with IEEE Big Data). DOI: 10.1109/BigData47090.2019.9006307.
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  9. Zhu J, Nolte AM, Jacobs N, Ye M. 2019. Incorporating Machine Learning with LiDAR for Delineating Sinkholes. In: Kentucky Water Resources Annual Symposium.
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