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Sahib Julka
Sahib Julka
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Preverjeni e-poštni naslov na uni-passau.de
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Leto
Recognition of echolalic autistic child vocalisations utilising convolutional recurrent neural networks
S Amiriparian, A Baird, S Julka, A Alcorn, S Ottl, S Petrović, E Ainger, ...
222018
Deep convolutional recurrent neural network for rare acoustic event detection
S Amiriparian, N Cummins, S Julka, B Schuller
Proc. DAGA, 1522-1525, 2018
162018
Day-ahead forecasting of the percentage of renewables based on time-series statistical methods
R Basmadjian, A Shaafieyoun, S Julka
Energies 14 (21), 7443, 2021
142021
Knowledge distillation with segment anything (sam) model for planetary geological mapping
S Julka, M Granitzer
International Conference on Machine Learning, Optimization, and Data Science …, 2023
112023
Lessons learned from the 1st Ariel Machine Learning Challenge: Correcting transiting exoplanet light curves for stellar spots
N Nikolaou, IP Waldmann, A Tsiaras, M Morvan, B Edwards, KH Yip, ...
RAS Techniques and Instruments 2 (1), 695-709, 2023
102023
Conditional generative adversarial networks for speed control in trajectory simulation
S Julka, V Sowrirajan, J Schloetterer, M Granitzer
International Conference on Machine Learning, Optimization, and Data Science …, 2021
52021
Spatio-temporal machine learning analysis of social media data and refugee movement statistics
C Havas, L Wendlinger, J Stier, S Julka, V Krieger, C Ferner, ...
ISPRS International Journal of Geo-Information 10 (8), 498, 2021
32021
Day-Ahead Forecasting of the Percentage of Renewables Based on Time-Series Statistical Methods. Energies 2021, 14, 7443
R Basmadjian, A Shaafieyoun, S Julka
s Note: MDPI stays neutral with regard to jurisdictional claims in published …, 2021
32021
Deep active learning for detection of mercury’s bow shock and magnetopause crossings
S Julka, N Kirschstein, M Granitzer, A Lavrukhin, U Amerstorfer
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022
22022
An active learning approach for automatic detection of bow shock and magnetopause crossing signatures in Mercury's magnetosphere using MESSENGER magnetometer observations.
S Julka
Proceedings of the 2nd Machine Learning in Heliophysics, 8, 2022
12022
Generative adversarial networks for automatic detection of mounds in digital terrain models (mars arabia terra)
S Julka, M Granitzer, B De Toffoli, L Penasa, R Pozzobon, U Amerstorfer
EGU General Assembly Conference Abstracts, EGU21-9188, 2021
12021
Deep Active Learning with Concept Drifts for Detection of Mercury’s Bow Shock and Magnetopause Crossings
S Julka, R Ishmukhametov, M Granitzer
International Conference on Machine Learning, Optimization, and Data Science …, 2023
2023
Automatic detection of bow shock and magnetopause boundaries at Mercury using MESSENGER magnetometer data
D Nevskii, A Lavrukhin, S Julka, D Parunakian, M Granitzer
44th COSPAR Scientific Assembly. Held 16-24 July 44, 475, 2022
2022
Determination of magnetopause and bow shock shape based on convolutional neural network modelling of MESSENGER data
A Lavrukhin, D Parunakian, D Nevsky, S Julka, M Granitzer, A Windisch, ...
European Planetary Science Congress, EPSC2021-651, 2021
2021
Echtzeit-Lagebild für effizientes Migrationsmanagement zur Gewährleistung humanitärer Sicherheit (HUMAN+); Teilvorhaben: Integrative Echtzeit Lage-und Vorhersagemodelle für …
M Granitzer, S Julka, J Stier, L Wendlinger
Universität Passau, 2020
2020
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