Titlebook: Engineering Applications of Neural Networks; 25th International C Lazaros Iliadis,Ilias Maglogiannis,Chrisina Jayne Conference proceedings

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Engineering Applications of Neural Networks978-3-031-62495-7Series ISSN 1865-0929 Series E-ISSN 1865-0937

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https://doi.org/10.1007/978-3-031-62495-7deep learning; generative AI; cybersecurity; data mining; machine learning; anomaly detection; recommendat

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Example Application of Scanning Mirrors,ent computational constraints. The main aim is to improve performance and outcomes by fine-tuning the LDA model’s alpha, beta, and topic parameters in the Mallet implementation. The difficulty comes from the time-consuming task of manually adjusting hyperparameters and the high computational expense

neologism

https://doi.org/10.1007/978-981-97-3295-1ng strong interest on artificial intelligence, particularly when the world of Internet-of-Things is considered. Managing and monitoring this data flow is crucial in machining processes, where the health of the system is assessed through the analysis of different sources, such as vibration, temperatu

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https://doi.org/10.1007/978-1-4615-4997-0. pam-4 encodes two bits of data using four different voltage levels. Compared to conventional NRZ (non-return-to-zero) encoding, which employs two voltage levels to represent one bit of information, pam-4 is a more effective technique to convey data. However, not every pam-4 sequence is equally eas

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https://doi.org/10.1007/978-1-4471-4597-4n recent years, many works and applications have observed the use of Artificial Intelligence-based models using Convolution Neural Networks (CNNs) to identify health problems using images. In our study, we searched for new architectures based on CNN using the Q-NAS algorithm. We compared its perform