Titlebook: Engineering Applications of Neural Networks; 18th International C Giacomo Boracchi,Lazaros Iliadis,Aristidis Likas Conference proceedings 2

FIR

Conference proceedings 2017n Athens, Greece, in August 2017.. .The 40 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 83 submissions. The papers cover the topics of deep learning, convolutional neural networks, image processing, pattern recognition, recommendation systems, ma

REP

Nina Bascia,Pamela Osmond-Johnsondetection as a major parameter of the problem. Our detection system is tested on the data corpora of PAN Webis intrinsic plagiarism detection’s shared tasks of 2009 and 2011 and is compared to the results of the highest score participations.

Senescent

Julia E. Morris,Wesley Imms,Adam DehringHCBC) features. The proposed method is compared with a baseline using mel-frequency cepstrum coefficients (MFCCs) and a state-of-the-art convolutional neural network (CNN) system. HCBC features result to be on par with CNN, while requiring less computation effort and memory space at the cost of being application specific.

Myocarditis

daredevil

Baby Cry Sound Detection: A Comparison of Hand Crafted Features and Deep Learning ApproachHCBC) features. The proposed method is compared with a baseline using mel-frequency cepstrum coefficients (MFCCs) and a state-of-the-art convolutional neural network (CNN) system. HCBC features result to be on par with CNN, while requiring less computation effort and memory space at the cost of being application specific.

WAX

CHART

A Neural Network Approach for Predicting the Diameters of Electrospun Polyvinylacetate (PVAc) Nanofi method, showing good performance in terms of both average RMSE (0.109, corresponding to 138.51?nm) and correlation coefficient (0.905) between the desired and the predicted diameters when a White Gaussian Noise with 2% power (WGN.) is applied to the interpolations.

justify

labile

HEW

A Spiking One-Class Anomaly Detection Framework for Cyber-Security on Industrial Control Systemsents an advanced .-. (SOCCADF) based on the . algorithm. This algorithm implements an innovative application of the .-. since it is trained exclusively with data that characterize the normal operation of ICS and it is able to detect divergent behaviors and abnormalities associated with APT attacks.