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Flexible Substrate
100%
Ferroelectric Field-effect Transistor (FeFET)
100%
Online Training
100%
Deep Neural Network Accelerator
100%
In Situ
50%
Nonlinearity
50%
Non-ideality
50%
Non-volatile
50%
Classification Accuracy
50%
Scalable Process
50%
Indian Institute of Technology
50%
National Institute of Standards
50%
Power Budget
50%
Deep Learning Architectures
50%
Synapse
50%
Dynamic Weight
50%
Network Training
50%
Deep Neural Network
50%
Ferroelectric Memory
50%
Analog Memory
50%
Weight Update
50%
Training Accuracy
50%
Data Retention
50%
Crossbar Array
50%
Matrix-vector multiplication
50%
Handwritten Dataset
50%
Memory Transistors
50%
Fully Scalable
50%
Bit Precision
50%
Training Experiment
50%
INIS
substrates
100%
accelerators
100%
neural networks
100%
field effect transistors
100%
ferroelectric materials
100%
accuracy
66%
data
33%
dynamics
33%
architecture
33%
implementation
33%
power
33%
transistors
33%
weight
33%
classification
33%
retention
33%
range
33%
nonlinear problems
33%
volatility
33%
matrices
33%
asymmetry
33%
precision
33%
datasets
33%
budgets
33%
vectors
33%
Engineering
Field-Effect Transistor
100%
Flexible Substrate
100%
Deep Neural Network
100%
Classification Accuracy
33%
Power Budget
33%
Neural Network Architecture
33%
Network Training
33%
Bit Precision
33%
Data Retention
33%
Matrix Multiplication
33%
Nonlinearity
33%
Computer Science
Back End
100%
Deep Neural Network
100%
Effect Transistor
100%
Neural Network Architecture
33%
Matrix Multiplication
33%
Classification Accuracy
33%
Material Science
Field Effect Transistors
100%
Ferroelectric Material
100%
Transistor
33%
Biochemistry, Genetics and Molecular Biology