5 citations · 28 across the 15 of their papers we have counts for
9 papers · 1 filter
Forecasting Sensor Values in Waste-To-Fuel Plants: a Case Study
Bor Brecelj, Beno Šircelj, Jože M. Rožanec +2
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…
Enriching Artificial Intelligence Explanations with Knowledge Fragments
Jože M. Rožanec, Elena Trajkova, Inna Novalija +4
Artificial Intelligence models are increasingly used in manufacturing to inform decision-making. Responsible decision-making requires accurate forecasts and an understanding of the…
Knowledge Modelling and Active Learning in Manufacturing
Jože M. Rožanec, Inna Novalija, d Patrik Zajec +2
The increasing digitalization of the manufacturing domain requires adequate knowledge modeling to capture relevant information. Ontologies and Knowledge Graphs provide means to mod…
A Review of Explainable Artificial Intelligence in Manufacturing
Georgios Sofianidis, Jože M. Rožanec, Dunja Mladenić +1
The implementation of Artificial Intelligence (AI) systems in the manufacturing domain enables higher production efficiency, outstanding performance, and safer operations, leveragi…
XAI-KG: knowledge graph to support XAI and decision-making in manufacturing
Jože M. Rožanec, Patrik Zajec, Klemen Kenda +3
The increasing adoption of artificial intelligence requires accurate forecasts and means to understand the reasoning of artificial intelligence models behind such a forecast. Expla…
STARdom: an architecture for trusted and secure human-centered manufacturing systems
Jože M. Rožanec, Patrik Zajec, Klemen Kenda +14
There is a lack of a single architecture specification that addresses the needs of trusted and secure Artificial Intelligence systems with humans in the loop, such as human-centere…
Semantic XAI for contextualized demand forecasting explanations
Jože M. Rožanec, Dunja Mladenić
The paper proposes a novel architecture for explainable AI based on semantic technologies and AI. We tailor the architecture for the domain of demand forecasting and validate it on…
Towards Active Learning Based Smart Assistant for Manufacturing
Patrik Zajec, Jože M. Rožanec, Inna Novalija +3
A general approach for building a smart assistant that guides a user from a forecast generated by a machine learning model through a sequence of decision-making steps is presented.…
Actionable Cognitive Twins for Decision Making in Manufacturing
Jože M. Rožanec, Jinzhi Lu, Jan Rupnik +5
Actionable Cognitive Twins are the next generation Digital Twins enhanced with cognitive capabilities through a knowledge graph and artificial intelligence models that provide insi…