A Comprehensive Study of MCS-TCL: Multi-Functional Sampling for Trustworthy Compressive Learning

Compressive Learning (CL) is an emerging paradigm that allows machine learning models to perform inference directly from compressed measurements, significantly reducing sensing and computational costs. While existing CL approaches have achieved competitive accuracy compared to traditional image-doma...

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Bibliographic Details

Published in:	Information
Main Authors:	Fuma Kimishima, Jian Yang, Jinjia Zhou
Format:	Article
Language:	English
Published:	MDPI AG 2025-09-01
Subjects:	compressive learning compressive sensing image classification evidential deep learning
Online Access:	https://www.mdpi.com/2078-2489/16/9/777