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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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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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Guozhe Yang, Qingze Tan, Zhiqiang Tian, Xingyu Jiang, Keqiang Chen, Yitao Lu, Weijun Liu and Peisheng Yuan
To cope with the problems of poor matching between processing characteristics and manufacturing resources, low production efficiency, and the hard-to-meet dynamic and changeable model requirements in multi-variety and small batch aerospace enterprises, a...
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Elena Martínez-Fernandez, Ignacio Rojas-Valenzuela, Olga Valenzuela and Ignacio Rojas
The diagnosis of different pathologies and stages of cancer using whole histopathology slide images (WSI) is the gold standard for determining the degree of tissue metastasis. The use of deep learning systems in the field of medical images, especially hi...
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Muhammad Ali Shafique, Arslan Munir and Joonho Kong
Deep learning is employed in many applications, such as computer vision, natural language processing, robotics, and recommender systems. Large and complex neural networks lead to high accuracy; however, they adversely affect many aspects of deep learning...
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