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010   $a3-030-80568-9
024 7 $a10.1007/978-3-030-80568-5
035   $a(CKB)5590000000516524
035   $a(MiAaPQ)EBC6675951
035   $a(Au-PeEL)EBL6675951
035   $a(OCoLC)1258668803
035   $a(DE-He213)978-3-030-80568-5
035   $a(PPN)258088109
035   $a(EXLCZ)995590000000516524
100   $a20210623d2021      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aProceedings of the 22nd Engineering Applications of Neural Networks Conference $eEANN 2021 /$fedited by Lazaros Iliadis, John Macintyre, Chrisina Jayne, Elias Pimenidis
205   $a1st ed. 2021.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021.
215   $a1 online resource (545 pages) $cillustrations (chiefly color)
225 1 $aProceedings of the International Neural Networks Society,$x2661-815X ;$v3
311 0 $a3-030-80567-0 
327   $aAutomatic Facial Expression Neutralisation Using Generative Adversarial Network -- Creating Ensembles of Generative Adversarial Network Discriminators for One-class Classification -- A Hybrid Deep Learning Ensemble for Cyber Intrusion Detection -- Anomaly Detection by Robust Feature Reconstruction -- Deep Learning of Brain Asymmetry Images and Transfer Learning for Early Diagnosis of Dementia -- Deep learning topology-preserving EEG-based images for autism detection in infants -- Improving the Diagnosis of Breast Cancer by Combining Visual and Semantic Feature Descriptors -- Liver cancer trait detection and classification through Machine Learning on smart mobile devices.
330   $aThis book contains the proceedings of the 22nd EANN ?Engineering Applications of Neural Networks? 2021 that comprise of research papers on both theoretical foundations and cutting-edge applications of artificial intelligence. Based on the discussed research areas, emphasis is given in advances of machine learning (ML) focusing on the following algorithms-approaches: Augmented ML, autoencoders, adversarial neural networks, blockchain-adaptive methods, convolutional neural networks, deep learning, ensemble methods, learning-federated learning, neural networks, recurrent ? long short-term memory. The application domains are related to: Anomaly detection, bio-medical AI, cyber-security, data fusion, e-learning, emotion recognition, environment, hyperspectral imaging, fraud detection, image analysis, inverse kinematics, machine vision, natural language, recommendation systems, robotics, sentiment analysis, simulation, stock market prediction.
410  0$aProceedings of the International Neural Networks Society,$x2661-815X ;$v3
606   $aComputational intelligence
606   $aEngineering$xData processing
606   $aArtificial intelligence
606   $aComputational Intelligence
606   $aData Engineering
606   $aArtificial Intelligence
615  0$aComputational intelligence.
615  0$aEngineering$xData processing.
615  0$aArtificial intelligence.
615 14$aComputational Intelligence.
615 24$aData Engineering.
615 24$aArtificial Intelligence.
676   $a006.32
702   $aIliadis$b Lazaros S.
712 12$aEANN (Conference)
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910488722503321
996   $aProceedings of the 22nd engineering applications of neural networks conference$92815816
997   $aUNINA