Zobrazeno 1 - 10
of 78
pro vyhledávání: '"Rožanec, Jože M."'
Autor:
Rožanec, Jože M., Petelin, Gašper, Costa, João, Bertalanič, Blaž, Cerar, Gregor, Guček, Marko, Papa, Gregor, Mladenić, Dunja
In many cases, a machine learning model must learn to correctly predict a few data points with particular values of interest in a broader range of data where many target values are zero. Zero-inflated data can be found in diverse scenarios, such as l
Externí odkaz:
http://arxiv.org/abs/2310.08088
Autor:
Suh, Sungho, Rey, Vitor Fortes, Bian, Sizhen, Huang, Yu-Chi, Rožanec, Jože M., Ghinani, Hooman Tavakoli, Zhou, Bo, Lukowicz, Paul
Manufacturing industries strive to improve production efficiency and product quality by deploying advanced sensing and control systems. Wearable sensors are emerging as a promising solution for achieving this goal, as they can provide continuous and
Externí odkaz:
http://arxiv.org/abs/2308.03514
Autor:
Rožanec, Jože M., Montini, Elias, Cutrona, Vincenzo, Papamartzivanos, Dimitrios, Klemenčič, Timotej, Fortuna, Blaž, Mladenić, Dunja, Veliou, Entso, Giannetsos, Thanassis, Emmanouilidis, Christos
Industrial revolutions have historically disrupted manufacturing by introducing automation into production. Increasing automation reshapes the role of the human worker. Advances in robotics and artificial intelligence open new frontiers of human-mach
Externí odkaz:
http://arxiv.org/abs/2307.05508
Autor:
Zajec, Patrik1,2 (AUTHOR), Rožanec, Jože M.1,2,3 (AUTHOR) joze.rozanec@ijs.si, Theodoropoulos, Spyros4,5 (AUTHOR), Fontul, Mihail6 (AUTHOR), Koehorst, Erik7 (AUTHOR), Fortuna, Blaž2,3 (AUTHOR), Mladenić, Dunja2 (AUTHOR)
Publikováno v:
International Journal of Production Research. Oct2024, Vol. 62 Issue 19, p6979-6998. 20p.
Autor:
Rožanec, Jože M., Zajec, Patrik, Theodoropoulos, Spyros, Koehorst, Erik, Fortuna, Blaž, Mladenić, Dunja
Industry 4.0 aims to optimize the manufacturing environment by leveraging new technological advances, such as new sensing capabilities and artificial intelligence. The DRAEM technique has shown state-of-the-art performance for unsupervised classifica
Externí odkaz:
http://arxiv.org/abs/2212.09352
Autor:
Rožanec, Jože M., Zajec, Patrik, Theodoropoulos, Spyros, Koehorst, Erik, Fortuna, Blaž, Mladenić, Dunja
Quality control is a crucial activity performed by manufacturing companies to ensure their products conform to the requirements and specifications. The introduction of artificial intelligence models enables to automate the visual quality inspection,
Externí odkaz:
http://arxiv.org/abs/2212.09317
Autor:
Rožanec, Jože M., Papamartzivanos, Dimitrios, Veliou, Entso, Anastasiou, Theodora, Keizer, Jelle, Fortuna, Blaž, Mladenić, Dunja
We propose using a two-layered deployment of machine learning models to prevent adversarial attacks. The first layer determines whether the data was tampered, while the second layer solves a domain-specific problem. We explore three sets of features
Externí odkaz:
http://arxiv.org/abs/2209.13963
In this research, we develop machine learning models to predict future sensor readings of a waste-to-fuel plant, which would enable proactive control of the plant's operations. We developed models that predict sensor readings for 30 and 60 minutes in
Externí odkaz:
http://arxiv.org/abs/2209.13957
Autor:
Rožanec, Jože M., Bizjak, Luka, Trajkova, Elena, Zajec, Patrik, Keizer, Jelle, Fortuna, Blaž, Mladenić, Dunja
Quality control is a crucial activity performed by manufacturing enterprises to ensure that their products meet quality standards and avoid potential damage to the brand's reputation. The decreased cost of sensors and connectivity enabled increasing
Externí odkaz:
http://arxiv.org/abs/2209.05486
Autor:
Rožanec, Jože M, Nemec, Bojan
One of the most important challenges in robotics is producing accurate trajectories and controlling their dynamic parameters so that the robots can perform different tasks. The ability to provide such motion control is closely related to how such mov
Externí odkaz:
http://arxiv.org/abs/2208.01903