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Training Radial Basis Function Neural Networks for Classification via Class-Specific Clustering
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Article)
In training radial basis function neural networks (RBFNNs), the locations of Gaussian neurons are commonly determined by clustering. Training inputs can be clustered on a fully unsupervised manner (input clustering), or ...
Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Article)
Early detection of the motor faults is essential and artificial neural networks are widely used for this purpose. The typical systems usually encapsulate two distinct blocks: feature extraction and classification. Such ...
Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks
(
Academic Press
, 2017 , Article)
Structural health monitoring (SHM) and vibration-based structural damage detection have been a continuous interest for civil, mechanical and aerospace engineers over the decades. Early and meticulous damage detection has ...
Learned vs. engineered features for fine-grained classification of aquatic macroinvertebrates
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Conference Paper)
Aquatic macroinvertebrate biomonitoring is an efficient way of assessment of slow and subtle anthropogenic changes and their effect on water quality. It is imperative to have reliable identification and counts of the various ...