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Exploring Asymmetric Autoencoder Architectures for Computationally Efficient Neural Image Compression

delete2026-04-01
delete0
PRE
AI
L
Leonardo Augusto
V
Vitor Arguilar
D
da Silveira, Thiago L. T.
G
Grellert, Mateus *
DOI：10.1109/MDAT.2025.3615794delete
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Abstract

Abstract

En
Keywords:
Computer architecture
Image coding
Computational modeling
Decoding
Kernel
Codecs
Autoencoders
Training
Complexity theory
Graphics processing units
Deep Neural Networks
Asymmetric Autoencoders
Image Compression

Journal

I
IEEE Design & Test
IF:
1.9
Papers:
39
Citations:
0

Organization

No organization information available