RADENN: A Domain-Specific Language for the Rapid Development of Neural Networks

RADENN: A Domain-Specific Language for the Rapid Development of Neural Networks

RADENN is a domain-specific language designed to rapidly develop fully connected neural networks for classification and regression problems. The primary objective of this language is to make neural network algorithms more accessible to a broader audience. RADENN is built on top of Keras API with Ten...

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Bibliographic Details
Main Authors: Israel Pineda, Dustin Carrion-Ojeda, Rigoberto Fonseca-Delgado
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Neural networks
domain-specific language
deep learning
Online Access:https://ieeexplore.ieee.org/document/10207040/

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