Emil Slusanschi
Cited by
Cited by
Automatic differentiation of the general-purpose computational fluid dynamics package FLUENT
CH Bischof, HM Bücker, A Rasch, E Slusanschi, B Lang
Efficient and accurate derivatives for a software process chain in airfoil shape optimization
CH Bischof, HM Bücker, B Lang, A Rasch, E Slusanschi
Future Generation Computer Systems 21 (8), 1333-1344, 2005
Sensitivity-based analysis of the k–ε model for the turbulent flow between two plates
A Bardow, CH Bischof, HM Bücker, G Dietze, R Kneer, A Leefken, ...
Chemical engineering science 63 (19), 4763-4775, 2008
Practical shape optimization of a levitation device for single droplets
E Groß-Hardt, E Slusanschi, HM Bücker, A Pfennig, CH Bischof
Optimization and Engineering 9 (2), 179-199, 2008
Data hiding using steganography
MA Dagadita, EI Slusanschi, R Dobre
2013 IEEE 12th International Symposium on Parallel and Distributed Computing …, 2013
Creating roadmaps in aerial images with generative adversarial networks and smoothing-based optimization
D Costea, A Marcu, E Slusanschi, M Leordeanu
Proceedings of the IEEE International Conference on Computer Vision …, 2017
Mapping data mining algorithms on a GPU architecture: a study
A Gainaru, E Slusanschi, S Trausan-Matu
International Symposium on Methodologies for Intelligent Systems, 102-112, 2011
Bounds for kullback-leibler divergence
PG Popescu, SS Dragomir, EI Sluşanschi, ON Stănăşilă
Electronic Journal of Differential Equations 2016, 2016
Algorithmic differentiation of Java programs.
EI Slusanschi
RWTH Aachen University, Germany, 2008
SafeUAV: Learning to estimate depth and safe landing areas for UAVs from synthetic data
A Marcu, D Costea, V Licaret, M Pîrvu, E Slusanschi, M Leordeanu
Proceedings of the European Conference on Computer Vision (ECCV), 0-0, 2018
Delayed propagation of derivatives in a two-dimensional aircraft design optimization problem
HM Bücker, A Rasch, E Slusanschi, CH Bischof
Proceedings of the 17th Annual International Symposium on High Performance …, 2003
A new upper bound for Shannon entropy. A novel approach in modeling of Big Data applications
PG Popescu, EI Sluşanschi, V Iancu, F Pop
Concurrency and Computation: Practice and Experience 28 (2), 351-359, 2016
A multi-stage multi-task neural network for aerial scene interpretation and geolocalization
A Marcu, D Costea, E Slusanschi, M Leordeanu
arXiv preprint arXiv:1804.01322, 2018
AAA-based infrastructure for industrial wireless sensor networks
N Oualha, A Olivereau, M Wehner, T Bartzsch, D Burggraf, S Zeisberg, ...
2012 Future Network & Mobile Summit (FutureNetw), 1-8, 2012
A trustworthy architecture for wireless industrial sensor networks: Research roadmap of EU TWISNet trust and security project
M Wehner, S Zeisberg, A Olivereau, N Oulha, L Gheorghe, E Slusanschi, ...
2011 First SysSec Workshop, 63-66, 2011
Sensitivities for a single drop simulation
CH Bischof, HM Bücker, A Rasch, E Slusanschi
International Conference on Computational Science, 888-896, 2003
A Multi-stage Multi-task neural network for aerial scene interpretation and geolocalization. arXiv, 2018
A Marcu, D Costea, E Slusanschi, M Leordeanu
arXiv preprint arXiv:1804.01322, 0
Using the integrated GPU to improve CPU sort performance
G Lupescu, EI Sluşanschi, N Tăpuş
2017 46th International Conference on Parallel Processing Workshops (ICPPW …, 2017
Bounds for Jeffreys–Tsallis and Jensen–Shannon–Tsallis divergences
PG Popescu, V Preda, EI Sluşanschi
Physica A: Statistical Mechanics and its Applications 413, 280-283, 2014
N-body simulations with GADGET-2
VL Spiridon, EI Slusanschi
2013 15th International Symposium on Symbolic and Numeric Algorithms for …, 2013
The system can't perform the operation now. Try again later.
Articles 1–20