Exploring the Knowledge Embedded in Class Visualizations and Their Application in Dataset and Extreme Model Compression

Exploring the Knowledge Embedded in Class Visualizations and Their Application in Dataset and Extreme Model Compression

Artificial neural networks are efficient learning algorithms that are considered to be universal approximators for solving numerous real-world problems in areas such as computer vision, language processing, or reinforcement learning. To approximate any given function, neural networks train a large n...

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Bibliographic Details
Main Authors: José Ricardo Abreu-Pederzini, Guillermo Arturo Martínez-Mascorro, José Carlos Ortíz-Bayliss, Hugo Terashima-Marín
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Applied Sciences
Subjects:
artificial neural networks
dataset compression
feature visualizations
knowledge distillation
mental imagery
model compression
Online Access:https://www.mdpi.com/2076-3417/11/20/9374

Internet

https://www.mdpi.com/2076-3417/11/20/9374

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