Kennedy, I. (2019). Distance Measures for Probabilistic Patterns
References
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Post, M., Fieguth, P., Naiel, M. A., Azimifar, Z., & Lamm, M. (2019). FRESCO: Fast Radiometric Egocentric Screen Compensation Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 0-0.
Hu, X., Naiel, M. A., Wong, A., Lamm, M., & Fieguth, P. (2019). RUNet: A Robust UNet Architecture for Image Super-Resolution Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 0-0.
Liu, L., Chen, J., Fieguth, P., Zhao, G., Chellappa, R., & Pietikäinen, M. (2019). From BoW to CNN: Two decades of texture representation for texture classification International Journal of Computer Vision, 127, 74-109.
Goetz, J., Fieguth, P., Kasiri, K., Bodin, X., Marcer, M., & Brenning, A. (2019). Accounting for permafrost creep in high-resolution snow depth mapping by modelling sub-snow ground deformation Remote Sensing of Environment, 231, 111275.
Pellegrino, N., Naiel, M. A., Lamm, M., & Fieguth, P. (2019). Sensitivity Assessment for Projector Camera Geometry Reconstruction Systems Journal of Computational Vision and Imaging Systems, 5, 1-1.
Chung, A., Fieguth, P., & Wong, A. (2018). Mitigating architectural mismatch during the evolutionary synthesis of deep neural networks ArXiv Preprint ArXiv:1811.07966.
Post, M., Fieguth, P., Naiel, M. A., Azimifar, Z., & Lamm, M. (2018). Fast radiometric compensation for nonlinear projectors Journal of Computational Vision and Imaging Systems, 4, 3-3.
Ma, B., Gawish, A., Wong, A., Fieguth, P., & Lamm, M. (2018). Real-time spatial-based resolution enhancement using shifted superposition