Full Forms in Deep Learning

Deep learning is a field which comes under Machine Learning.

In this blog post, we have listed all the important full forms used in Deep Learning. Deep learning is a subset of machine learning, which is essentially a neural network with three or more layers.

LIST OF TERMS AND ABBREVIATIONS in Deep Learning.

TermsAbbreviations
AHCRArabic Handwritten Character Recognition
CCRChinese Character Recognition
CNNConvolutional Neural Networks
DBNDeep Belief Network
DNNDeep Neural Network
HCRHandwritten Character Recognition
ILSVRCImageNet Large Scale Visual Recognition Challenge
ISIDCHARIndian Statistical Institute Devanagiri Character Database
MCDNNMulti Column Deep Neural Network
NLPRNational Laboratory of Pattern Recognition
OCROptical Character Recognition
SVMSupport Vector Machines
VGGVisual Geometry Group
AE Auto-Encoder 
AI Artificial intelligence 
ANNArtificial Neural Networks
AUC Area-under-the-receiver operation characteristics curve 
AUC-PR Area-under-the-precision–recall curve 
BRNN Bidirectional recurrent neural network 
CAE Convolutional auto-encoder 
CCSDCoupled-Cluster Singles Doubles with perturbative triples
CGCNNCrystal Graph Convolutional Neural Networks
CNN Convolutional neural network 
DBN Deep belief network 
DNN Deep neural network 
DST-NN Deep spatio-temporal neural network 
ECG Electrocardiography 
ECoG Electrocorticography 
EEG Electroencephalography 
EMG Electromyography 
EOG Electrooculography 
GCNNGraph Convolutional Neural Network
GRU Gated recurrent unit 
LSTM Long short-term memory 
MD-RNN Multi-dimensional recurrent neural network 
MLP Multilayer perceptron 
MRI Magnetic resonance image 
PCA Principal component analysis 
PET Positron emission tomography 
PSSM Position specific scoring matrix 
RBM Restricted Boltzmann machine 
ReLU Rectified linear unit 
RNN Recurrent neural network 
SAE Stacked auto-encoder 
SGD Stochastic gradient descent 
SMILESSimplified Molecular Input Line Entry System
AE Auto-Encoder 
AI Artificial intelligence 
ANNArtificial Neural Networks
AUC Area-under-the-receiver operation characteristics curve 
AUC-PR Area-under-the-precision–recall curve 
BRNN Bidirectional recurrent neural network 
CAE Convolutional auto-encoder 
CCSDCoupled-Cluster Singles Doubles with perturbative triples
CGCNNCrystal Graph Convolutional Neural Networks
CNN Convolutional neural network 
DBN Deep belief network 
DNN Deep neural network 
DST-NN Deep spatio-temporal neural network 
ECG Electrocardiography 
ECoG Electrocorticography 
EEG Electroencephalography 
EMG Electromyography 
EOG Electrooculography 
GCNNGraph Convolutional Neural Network
GRU Gated recurrent unit 
LSTM Long short-term memory 
MD-RNN Multi-dimensional recurrent neural network 
MLP Multilayer perceptron 
MRI Magnetic resonance image 
PCA Principal component analysis 
PET Positron emission tomography 
PSSM Position specific scoring matrix 
RBM Restricted Boltzmann machine 
ReLU Rectified linear unit 
RNN Recurrent neural network 
SAE Stacked auto-encoder 
SGD Stochastic gradient descent 
SMILESSimplified Molecular Input Line Entry System

Leave a Comment