| Wavelet packets approach to blind separation of statistically dependent sources I Kopriva, D Seršić Neurocomputing 71 (7-9), 1642-1655, 2008 | 55 | 2008 |
| How to teach basic university-level programming concepts to first graders? A Sović, T Jagušt, D Seršić Integrated STEM Education Conference (ISEC), 1-6, 2014 | 37 | 2014 |
| A short introduction to tensor-based methods for factor analysis and blind source separation L De Lathauwer, S Loncaric, G Ramponi, D Sersic Proc. of the 7th International Symposium on image and signal processing and …, 2011 | 34 | 2011 |
| Signal decomposition methods for reducing drawbacks of the DWT A Sović, D Seršić Engineering Review: Međunarodni časopis namijenjen publiciranju originalnih …, 2012 | 33 | 2012 |
| Adaptive 2-D wavelet transform based on the lifting scheme with preserved vanishing moments M Vrankic, D Sersic, V Sucic IEEE Transactions on Image Processing 19 (8), 1987-2004, 2010 | 29 | 2010 |
| Using robotics to foster creativity in early gifted education T Jagust, J Cvetkovic-Lay, AS Krzic, D Sersic International Conference on Robotics and Education RiE 2017, 126-131, 2017 | 27 | 2017 |
| Adaptive spatio-temporal denoising of fluoroscopic X-ray sequences M Tomic, S Loncaric, D Sersic Biomedical signal processing and control 7 (2), 173-179, 2012 | 26 | 2012 |
| A novel approach to wheeze detection A Alic, I Lackovic, V Bilas, D Sersic, R Magjarevic World Congress on Medical Physics and Biomedical Engineering 2006: August 27 …, 2007 | 21 | 2007 |
| L1 minimization using recursive reduction of dimensionality AS Kržić, D Seršić Signal Processing 151, 119-129, 2018 | 19 | 2018 |
| Performance analysis of the LPA-RICI denoising method J Lerga, V Sucic, D Sersic 2009 Proceedings of 6th International Symposium on Image and Signal …, 2009 | 16 | 2009 |
| Statistical compressive sensing for efficient signal reconstruction and classification I Ralašič, A Tafro, D Seršič 2018 4th International Conference on Frontiers of Signal Processing (ICFSP …, 2018 | 15 | 2018 |
| Edge-preserving adaptive wavelet denoising using ICI rule M Tomic, D Sersic, M Vrankic Electronics letters 44 (11), 698-699, 2008 | 15 | 2008 |
| Wavelet filter banks with adaptive number of zero moments D Sersic WCC 2000-ICSP 2000. 2000 5th International Conference on Signal Processing …, 2000 | 15 | 2000 |
| Sampling and reconstruction of sparse signals in shift-invariant spaces: Generalized Shannon’s theorem meets compressive sensing T Vlašić, D Seršić IEEE transactions on signal processing 70, 438-451, 2022 | 14 | 2022 |
| Off-the-shelf measurement setup for compressive imaging I Ralašić, D Seršić, D Petrinović IEEE Transactions on Instrumentation and Measurement 68 (2), 502-511, 2018 | 13 | 2018 |
| A realization of wavelet filter bank with adaptive filter parameters D Seršić Proc. EUSPICO, 1733-1736, 2000 | 13 | 2000 |
| Wavelet analysis of hydrological signals on an example of the River Sava A Sović, K Potočki, D Seršić, N Kuspilić 2012 Proceedings of the 35th International Convention MIPRO, 1042-1047, 2012 | 11 | 2012 |
| Rule-based EEG classifier utilizing local entropy of time–frequency distributions J Lerga, N Saulig, L Stanković, D Seršić Mathematics 9 (4), 451, 2021 | 10 | 2021 |
| Perceptual autoencoder for compressive sensing image reconstruction I Ralašić, D Seršić, S Šegvić Informatica 31 (3), 561-578, 2020 | 9 | 2020 |
| Spline-like Chebyshev polynomial model for compressive imaging T Vlašić, I Ralašić, A Tafro, D Seršić Journal of visual communication and image representation 66, 102731, 2020 | 9 | 2020 |
