References
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Hryniowski, A. (2018). A Content Enhancement Framework for Multi-Projector Systems
Hu, X., Naiel, M. A., Azimifar, Z., Ben Daya, I., Lamm, M., & Fieguth, P. (2018). Text enhancement in projected imagery Journal of Computational Vision and Imaging Systems, 4, 3-3.
Chung, A., Fieguth, P., & Wong, A. (2018). Nature vs. nurture: The role of environmental resources in evolutionary deep intelligence 2018 15th Conference on Computer and Robot Vision (CRV), 368-374. IEEE.
Bello-Cerezo, R., Fieguth, P., & Bianconi, F. (2018). LBP-motivated colour texture classification Proceedings of the European Conference on Computer Vision (ECCV), 0-0.
Sankar, V., Gawish, A., Fieguth, P., & Lamm, M. (2018). Understanding Blur and Model Learning in Projector Compensation Journal of Computational Vision and Imaging Systems, 4, 3-3.
Carter, K., Haines, L., MacLellan, B., Kralj, O., Gawish, A., Fieguth, P., … Bizheva, K. K. (2017). Quantitative Analysis of Epithelial and Total Corneal Thickness in Keratoconus using Sub-Micrometer Axial Resolution Optical Coherence Tomography Investigative Ophthalmology & Visual Science, 58, 3517-3517.
Liu, L., Fieguth, P., Guo, Y., Wang, X., & Pietikäinen, M. (2017). Local binary features for texture classification: Taxonomy and experimental study Pattern Recognition, 62, 135-160.
Shafiee, J. (2017). Randomly-connected Non-Local Conditional Random Fields