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Training Radial Basis Function Neural Networks for Classification via Class-Specific Clustering
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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 ...
Active vibration control of flexible cantilever plates using piezoelectric materials and artificial neural networks
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Academic Press
, 2016 , Article)
The study presented in this paper introduces a new intelligent methodology to mitigate the vibration response of flexible cantilever plates. The use of the piezoelectric sensor/actuator pairs for active control of plates ...
Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks
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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
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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 ...
Revealing the hidden features in traffic prediction via entity embedding
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Springer London
, 2019 , Article)
Models based on neural networks (NN) have been used widely and successfully in traffic prediction resulting in improved accuracy and efficiency in traffic flow, speed, passenger flow, and delay. Input data include continuous ...
Handcrafted features with convolutional neural networks for detection of tumor cells in histology images
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IEEE Computer Society
, 2016 , Conference Paper)
Detection of tumor nuclei in cancer histology images requires sophisticated techniques due to the irregular shape, size and chromatin texture of the tumor nuclei. Some very recently proposed methods employ deep convolutional ...
Towards enhanced control of upper prosthetic limbs: A force-myographic approach
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IEEE Computer Society
, 2016 , Conference Paper)
Reliable decoding of a user's intention is a key step to control prosthetic devices. Force myography (FMG) is often used to assess topographic force patterns resulting from volumetric changes of activated muscles. However, ...
Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images
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Institute of Electrical and Electronics Engineers Inc.
, 2016 , Article)
Detection and classification of cell nuclei in histopathology images of cancerous tissue stained with the standard hematoxylin and eosin stain is a challenging task due to cellular heterogeneity. Deep learning approaches ...
Learned vs. engineered features for fine-grained classification of aquatic macroinvertebrates
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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 ...
A grid-connected cascaded H-bridge multilevel converter with quasi seven-level Selective Harmonic Elimination
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Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
In this paper, a high power grid-connected cascaded H-bridge multilevel inverter (CHB-MLI) operating with Selective Harmonic Elimination (SHE) is presented complying with the low switching frequency operation limitation. ...