scholarly journals Rule-Based methods and Deep Learning Networks for Automatic Classification of ECG

2020 ◽  
Author(s):  
giovanni bortolan ◽  
Ivaylo Christov ◽  
Iana Simova
Keyword(s):  
Deep Learning ◽  
Automatic Classification ◽  
Learning Networks ◽  
Rule Based

Automatic classification of EEG signals via deep learning

2021 ◽  
Author(s):  
Tao Wu ◽  
Xiangzeng Kong ◽  
Yiwen Wang ◽  
Xue Yang ◽  
Jingxuan Liu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Automatic Classification ◽  
Eeg Signals

A Similarity-Based Object Classification Using Deep Neural Networks

2019 ◽  
pp. 197-219
Author(s):  
Parvathi R. ◽  
Pattabiraman V.
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Deep Neural Network ◽  
Search Algorithm ◽  
Random Projection ◽  
Learning Networks ◽  
Learning Models ◽  
External Conditions ◽  
And Training

This chapter proposes a hybrid method for classification of the objects based on deep neural network and a similarity-based search algorithm. The objects are pre-processed with external conditions. After pre-processing and training different deep learning networks with the object dataset, the authors compare the results to find the best model to improve the accuracy of the results based on the features of object images extracted from the feature vector layer of a neural network. RPFOREST (random projection forest) model is used to predict the approximate nearest images. ResNet50, InceptionV3, InceptionV4, and DenseNet169 models are trained with this dataset. A proposal for adaptive finetuning of the deep learning models by determining the number of layers required for finetuning with the help of the RPForest model is given, and this experiment is conducted using the Xception model.

Toward an Automatic Classification of SEM Images of Nanomaterials via a Deep Learning Approach

2019 ◽  
pp. 61-72 ◽  
Author(s):  
Cosimo Ieracitano ◽  
Fabiola Pantó ◽  
Nadia Mammone ◽  
Annunziata Paviglianiti ◽  
Patrizia Frontera ◽  
...  
Keyword(s):  
Deep Learning ◽  
Automatic Classification ◽  
Learning Approach ◽  
Sem Images
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