Article

A Hybrid Neural Framework for Robust Image Analysis under Data and Sensor Constraints

2026-03-31

Abstract excerpt

This paper proposes a novel, theoretically rigorous deep learning framework designed to maintain high classification and estimation accuracy in environments where standard RGB data is insufficient, corrupted, or unavailable. While state-of-the-art Convolutional Neural Networks (CNNs) excel in varied visual recognition tasks, they often struggle with domain shifts-such as those found in thermal, depth, or low-light...

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Literature Corpus work: 7d3c7895-304a-51af-9d8e-953ab290a663
DOI: 10.22541/au.177499046.64252450/v1

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