E-LIB Suche - Ergebnisse für: Rožanec, Jože

1

Go-Network: a graph sampling library written in Go:

, In: Companion of the 15th ACM/SPEC International Conference on Performance Engineering,

Rožanec, Jože M. ; Rožanec, Matias - p. 151-155 , 2024

Link: https://dl.acm.org/doi/1..

2

Worker Activity Recognition in Manufacturing Line Using Nea..:

Suh, Sungho ; Rey, Vitor Fortes ; Bian, Sizhen...
IEEE Internet of Things Journal. 11 (2024) 7 - p. 11554-11565 , 2024

Link: https://doi.org/10.1109/..

3

An Extensive Characterization of Graph Sampling Algorithms:

, In: Companion of the 15th ACM/SPEC International Conference on Performance Engineering,

S. Dizaji, S. Haleh ; Rozanec, Joze M. ; Farahani, Reza.. - p. 135-140 , 2024

Link: https://dl.acm.org/doi/1..

4

On-the-fly image-level oversampling for imbalanced datasets..:

Theodoropoulos, Spyros ; Zajec, Patrik ; Rožanec, Jože M...
Machine Learning. 113 (2024) 7 - p. 4013-4035 , 2024

Link: https://doi.org/10.1007/..

5

Adaptive explainable artificial intelligence for visual def..:

Rožanec, Jože M. ; Šircelj, Beno ; Fortuna, Blaž.
Procedia Computer Science. 232 (2024) - p. 3034-3043 , 2024

Link: https://doi.org/10.1016/..

6

Enhancing robustness to novel visual defects through StyleG..:

Theodoropoulos, Spyros ; Dardanis, Dimitrios ; Makridis, Georgios...
Journal of Intelligent Manufacturing. , 2024

Link: https://doi.org/10.1007/..

7

Few-shot learning for defect detection in manufacturing:

Zajec, Patrik ; Rožanec, Jože M. ; Theodoropoulos, Spyros...
International Journal of Production Research. , 2024

Link: https://doi.org/10.1080/..

8

Manufacturing workers fatigue: an exploratory study on pred..:

Emmanouilidis, Christos ; Montini, Elias ; Cutrona, Vincenzo.
https://research.rug.nl/en/publications/51c98e2d-19eb-4300-90d6-e3b512252144. , 2024

Link: https://hdl.handle.net/1..

9

Workers Fatigue Monitoring for Well-being Improvement in Ma..:

Rosselli, Michel ; Cutrona, Vincenzo ; Dell'Oca, Samuele...
https://research.rug.nl/en/publications/ff6c7ed6-1119-4c7d-9dad-e94ef51dffe7. , 2024

Link: https://hdl.handle.net/1..

10

The Graph-Massivizer Approach Toward a European Sustainable..:

, In: 2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC),

Molan, Martin ; Khan, Junaid Ahmed ; Bartolini, Andrea... - p. 1459-1464 , 2023

Link: https://doi.org/10.1109/..

11

An Information-Centric Perspective on Data:

Rožanec, Jože M. ; Montero Santos, Lola ; Delinavelli, Giacomo
Jože M. ROŽANEC, Lola MONTERO SANTOS & Giacomo DELINAVELLI, 'An information-centric perspective on data' (16th International Technology Transfer Conference, Ljubljana, October 11th 2023). , 2023

Link: https://ssrn.com/abstrac..

12

Semi-Supervised Event Predictions with Graph Networks:

, In: Companion of the 2023 ACM/SPEC International Conference on Performance Engineering,

Nemec, Peter ; Leban, Gregor ; Rozanec, Joze. - p. 245-246 , 2023

Link: https://dl.acm.org/doi/1..

13

AI, What Does the Future Hold for Us? Automating Strategic ..:

, In: Companion of the 2023 ACM/SPEC International Conference on Performance Engineering,

Rozanec, Joze ; Nemec, Peter ; Leban, Gregor. - p. 247-248 , 2023

Link: https://dl.acm.org/doi/1..

14

Graph-Scrutinizer: Towards Massive Graph Analytics and Reas..:

, In: Companion of the 2023 ACM/SPEC International Conference on Performance Engineering,

Rozanec, Joze ; Cochez, Michael ; van Bakel, Ruud.. - p. 251-252 , 2023

Link: https://dl.acm.org/doi/1..

15

Graph-Inceptor: Towards Extreme Data Ingestion, Massive Gra..:

, In: Companion of the 2023 ACM/SPEC International Conference on Performance Engineering,

Rozanec, Joze ; Elvesæter, Brian ; Roman, Dumitru.. - p. 253-254 , 2023

Link: https://dl.acm.org/doi/1..