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Marko Jankovic
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2020 – today
- 2024
- [c9]Mehmed Yüksel, Wiebke Brinkmann, Marko Jankovic, Hilmi Dogu Küçüker, Frank Kirchner:
Enhanced multifunctional interface for reconfigurability of robotic teams in planetary applications. ICRA 2024: 13509-13515 - 2020
- [c8]Marko Bajec, Marko Jankovic, Slavko Zitnik, Iztok Lebar Bajec:
Punctuation Restoration System for Slovene Language. RCIS 2020: 509-514 - [i1]Marko Jankovic, Mehmed Yüksel, Mohammad Mohammadzadeh Babr, Francesca Letizia, Vitali Braun:
Space Debris Ontology for ADR Capture Methods Selection. CoRR abs/2004.08866 (2020)
2010 – 2019
- 2019
- [j4]Marko Jankovic, Slavko Zitnik, Marko Bajec:
Reconstructing de facto software development methods. Comput. Sci. Inf. Syst. 16(1): 75-104 (2019) - 2015
- [c7]Marko Jankovic, Marko Bajec:
Comparison of software repositories for their usability in software process reconstruction. RCIS 2015: 298-308 - [c6]Predrag Ninkovic
, Marko Jankovic:
A novel power-line oriented DFT method with error elimination at off-line frequency operation. TSP 2015: 490-494 - 2013
- [c5]Ghazaleh Khodabandelou, Charlotte Hug, Rébecca Deneckère, Camille Salinesi, Marko Bajec, Elena Kornyshova, Marko Jankovic:
Cots Products To Trace Method Enactment: Review And Selection. ECIS 2013: 50 - [c4]Marko Jankovic, Marko Bajec, Ghazaleh Khodabandelou, Rébecca Deneckère, Charlotte Hug, Camille Salinesi:
Intelligent Agile Method Framework. ENASE 2013: 232-237 - [c3]Marko Jankovic:
Semi-automatic improvement of software development methods: Doctoral consortium paper. RCIS 2013: 1-6
2000 – 2009
- 2007
- [c2]Marko Jankovic
Modified Modulated Hebb-Oja Learning Rule: A Method for Biologically Plausible Principal Component Analysis. ICONIP (1) 2007: 527-536 - [c1]Andrzej Cichocki
Sparse Super Symmetric Tensor Factorization. ICONIP (1) 2007: 781-790 - 2006
- [j3]Marko Jankovic
Modulated Hebb-Oja learning Rule-a method for principal subspace analysis. IEEE Trans. Neural Networks 17(2): 345-356 (2006) - 2004
- [j2]Marko Jankovic, Hidemitsu Ogawa:
Time-oriented hierarchical method for computation of principal components using subspace learning algorithm. Int. J. Neural Syst. 14(5): 313-323 (2004) - 2003
- [j1]Marko Jankovic, Hidemitsu Ogawa:
A New Modulated Hebbian Learning Rule - Biologically Plausible Method for Local Computation of a Principal Subspace. Int. J. Neural Syst. 13(4): 215-223 (2003)
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last updated on 2024-08-20 22:50 CEST by the dblp team
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