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Norah Fahd Alhussainan, Belgacem Ben Youssef and Mohamed Maher Ben Ismail
Brain tumor diagnosis traditionally relies on the manual examination of magnetic resonance images (MRIs), a process that is prone to human error and is also time consuming. Recent advancements leverage machine learning models to categorize tumors, such a...
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Federico Ricci, Luca Petrucci, Francesco Mariani and Carlo Nazareno Grimaldi
The control of internal combustion engines is becoming increasingly challenging to the customer?s requirements for growing performance and ever-stringent emission regulations. Therefore, significant computational efforts are required to manage the large ...
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Alexander Hinterleitner, Richard Schulz, Lukas Hans, Aleksandr Subbotin, Nils Barthel, Noah Pütz, Martin Rosellen, Thomas Bartz-Beielstein, Christoph Geng and Phillip Priss
Cyber-Physical Systems (CPS) play an essential role in today?s production processes, leveraging Artificial Intelligence (AI) to enhance operations such as optimization, anomaly detection, and predictive maintenance. This article reviews a cognitive archi...
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Ya-Hui Chang, Chih-Wei Tseng and Hsien-Chieh Hsu
Urban stormwater drainage systems, which include many personholes to collect and discharge precipitation within a city, are extensively constructed to prevent streets and buildings from flooding. This research intends to build a machine learning model to...
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Justin Edwards and Mohamed El-Sharkawy
Semantic segmentation is a machine learning task that is seeing increased utilization in multiple fields, from medical imagery to land demarcation and autonomous vehicles. A real-time autonomous system must be lightweight while maintaining reasonable acc...
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