Work

Dimensionality reduction for AI based hyperspectral image classification based on XAI

Year: 2026

Type: preprint

Abstract: This research addresses the challenge of limited material recycling in wood recycling processes by leveraging artificial intelligence (AI)-based dimensionality reduction. Our study explores the application of convolutional neural networks (CNNs) in multi-channel hyperspectral imaging (HSI), extending beyond RGB channels to over 200 spectral channels. Dimensionality reduction within this context involves streamlining the feature space for AI system training and inference. Focusing on explainable AI (XAI) methods, this paper contributes to a broader research initiative, presenting a solution framework that enhances the sustainability and efficiency of wood recycling processes.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2609.22333

Authors: Zeljković, Vladimir, Stojanović, Branka, Ganster, Harald, Nešković, Aleksandar

Institutions: Joanneum Research, University of Belgrade

Topic: Remote-Sensing Image Classification

Subfield: Media Technology

Field: Engineering

Domain: Physical Sciences

SDG: Responsible consumption and production

Open Access status: green

OpenAlex ID: W7214045705

Cites:

Cited by:

Related to: