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pro vyhledávání: '"Kalach, Fadi El"'
Autor:
Prasad, Renjith, Shyalika, Chathurangi, Zand, Ramtin, Kalach, Fadi El, Venkataramanan, Revathy, Harik, Ramy, Sheth, Amit
Anomaly detection in manufacturing pipelines remains a critical challenge, intensified by the complexity and variability of industrial environments. This paper introduces AssemAI, an interpretable image-based anomaly detection system tailored for sma
Externí odkaz:
http://arxiv.org/abs/2408.02181
Rare events are occurrences that take place with a significantly lower frequency than more common regular events. In manufacturing, predicting such events is particularly important, as they lead to unplanned downtime, shortening equipment lifespan, a
Externí odkaz:
http://arxiv.org/abs/2407.01644
Autor:
Harik, Ramy, Kalach, Fadi El, Samaha, Jad, Clark, Devon, Sander, Drew, Samaha, Philip, Burns, Liam, Yousif, Ibrahim, Gadow, Victor, Tarekegne, Theodros, Saha, Nitol
Two industry-grade datasets are presented in this paper that were collected at the Future Factories Lab at the University of South Carolina on December 11th and 12th of 2023. These datasets are generated by a manufacturing assembly line that utilizes
Externí odkaz:
http://arxiv.org/abs/2401.15544
Autor:
Shyalika, Chathurangi, Roy, Kaushik, Prasad, Renjith, Kalach, Fadi El, Zi, Yuxin, Mittal, Priya, Narayanan, Vignesh, Harik, Ramy, Sheth, Amit
Publikováno v:
Sensors (14248220); May2024, Vol. 24 Issue 10, p3244, 25p
Akademický článek
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