Lazaros (Hrsg.) Iliadis
Proceedings of the 22nd Engineering Applications of Neural Networks Conference
EANN 2021
Ebook (PDF Format)
This book contains the proceedings of the 22nd EANN Engineering Applications of Neural Networks 2021 that comprise of research papers on both theoretical foundations and cutting-edge applications of artificial intelligence. Based on the discussed research areas, emphasis is given in advances of machine learning (ML) focusing on the following algorithms-approaches: Augmented ML, autoencoders, adversarial neural networks, blockchain-adaptive methods, convolutional neural networks, deep learning, ensemble methods, learning-federated learning, neural networks, recurrent - long short-term memory. The application domains are related to: Anomaly det…
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Beschreibung
This book contains the proceedings of the 22nd EANN Engineering Applications of Neural Networks 2021 that comprise of research papers on both theoretical foundations and cutting-edge applications of artificial intelligence. Based on the discussed research areas, emphasis is given in advances of machine learning (ML) focusing on the following algorithms-approaches: Augmented ML, autoencoders, adversarial neural networks, blockchain-adaptive methods, convolutional neural networks, deep learning, ensemble methods, learning-federated learning, neural networks, recurrent - long short-term memory. The application domains are related to: Anomaly detection, bio-medical AI, cyber-security, data fusion, e-learning, emotion recognition, environment, hyperspectral imaging, fraud detection, image analysis, inverse kinematics, machine vision, natural language, recommendation systems, robotics, sentiment analysis, simulation, stock market prediction.
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Produktdetails
Weitere Autoren: Macintyre, John (Hrsg.) / Jayne, Chrisina (Hrsg.) / Pimenidis, Elias (Hrsg.)
- ISBN: 978-3-030-80568-5
- EAN: 9783030805685
- Produktnummer: 36796713
- Verlag: Springer International Publishing
- Sprache: Englisch
- Erscheinungsjahr: 2021
- Seitenangabe: 521 S.
- Plattform: PDF
- Masse: 47'607 KB
- Auflage: 1st ed. 2021
- Reihenbandnummer: 3
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