Linear Progressive Coding for Semantic Communication using Deep Neural Networks

Eva Riherd; Raghu Mudumbai; Weiyu Xu

doi:10.1109/CISS59072.2024.10480188

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Conference proceeding

Linear Progressive Coding for Semantic Communication using Deep Neural Networks

Eva Riherd, Raghu Mudumbai and Weiyu Xu

2024 58th Annual Conference on Information Sciences and Systems (CISS), pp.1-6

03/13/2024

DOI: 10.1109/CISS59072.2024.10480188

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Abstract

We propose a novel linear progressive coding framework for obtaining hierarchical compressed representations (measurements) of data so that we can perform hierarchical-grain-level machine learning tasks timely and accurately using these representations. We first encode data into optimized low-rate coarse linear representations or measurements, which can be quickly communicated to the receiver and used for timely and accurate coarse-level classifications. We then design an additional set of optimized linear measurements or representations of the data so that the receiver can perform accurate finer-level classifications using these newly communicated representations together with the previously received coarse representations. Our proposed method can be considered as optimized hierarchical compressed learning or progressive semantic communications optimized for hierarchical-grain-level machine learning tasks, using low-cost linear measurements. Our experimental results on the MNIST and CIFAR-10 datasets show the linear progressive measurements enable timely performing coarse-level machine learning tasks with a small number of initial measurements, while for finer-level tasks, achieving overall accuracy and efficiency comparable to non-progressive methods.

Machine Learning

Semantics

classification

compressed learning

compressed sensing

Image coding

neural network

Pattern classification

Receivers

semantic communication

Signal reconstruction

Source coding

Details

Title: Subtitle: Linear Progressive Coding for Semantic Communication using Deep Neural Networks
Creators: Eva Riherd - University of Iowa
Raghu Mudumbai - University of Iowa,Department of Electrical and Computer Engineering,Iowa City,Iowa,USA,52240
Weiyu Xu - University of Iowa
Resource Type: Conference proceeding
Publication Details: 2024 58th Annual Conference on Information Sciences and Systems (CISS), pp.1-6
Publisher: IEEE
DOI: 10.1109/CISS59072.2024.10480188
eISSN: 2837-178X
Language: English
Date published: 03/13/2024
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984621359702771

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