Ghent University Academic Bibliography

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Highly parallel steered mixture-of-experts rendering at pixel-level for image and light field data

Vasileios Avramelos, Ruben Verhack, Ignace Saenen (UGent) , Glenn Van Wallendael (UGent) , Bart Goossens (UGent) and Peter Lambert (UGent)

(2020) JOURNAL OF REAL-TIME IMAGE PROCESSING. 17(4). p.931-947
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Influence of study design on digital pathology image quality evaluation : the need to define a clinical task

Ljiljana Platisa (UGent) , Leen Van Brantegem (UGent) , Asli Kumcu (UGent) , Richard Ducatelle (UGent) and Wilfried Philips (UGent)

(2017) JOURNAL OF MEDICAL IMAGING. 4(2).
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Compression parameters tuning for automatic image optimization in web applications

Hrvoje Leventić, Krešimir Nenadić, Irena Galić and Časlav Livada

(2016) PROCEEDINGS OF ELMAR 2016 - 58TH INTERNATIONAL SYMPOSIUM ELMAR 2016. p.181-184
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The student-t mixture as a natural image patch prior with application to image compression

Aäron van den Oord (UGent) and Benjamin Schrauwen (UGent)

(2014) JOURNAL OF MACHINE LEARNING RESEARCH. 15. p.2061-2086
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Learning a piecewise linear transform coding scheme for images

Aäron van den Oord (UGent) , Sander Dieleman (UGent) and Benjamin Schrauwen (UGent)

(2013) Proceedings of SPIE, the International Society for Optical Engineering. In Proceedings of SPIE 8768.
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Noise- and compression-robust biological features for texture classification

Gaëtan Martens (UGent) , Chris Poppe (UGent) , Peter Lambert (UGent) and Rik Van de Walle (UGent)

(2010) VISUAL COMPUTER. 26(6-8). p.915-922
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Model-based sparsity projection pursuit for lattice vector quantization

L. Fonteles, M. Antonini and Ronald Phlypo (UGent)

(2008) International Conference on Acoustics Speech and Signal Processing (ICASSP). p.1205-1208

Academic Bibliography

Highly parallel steered mixture-of-experts rendering at pixel-level for image and light field data

Influence of study design on digital pathology image quality evaluation : the need to define a clinical task

Compression parameters tuning for automatic image optimization in web applications

The student-t mixture as a natural image patch prior with application to image compression

Learning a piecewise linear transform coding scheme for images

Noise- and compression-robust biological features for texture classification

Model-based sparsity projection pursuit for lattice vector quantization

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