A Lightweight Support-Vector-Machine-Based Infrared Image Processing Workflow for Photovoltaic Module Thermal Anomaly Screening

Deep networks dominate photovoltaic (PV) thermographic fault detection but need large annotated datasets and resist interpretation. We present a lightweight, interpretable infrared workflow combining support-vector-machine (SVM) module/background segmentation from four handcrafted features with an a...

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Bibliografske podrobnosti

Principais autores:	Vladimír Szomosi, Stanislav Baňački, Július Šimčák, Marek Bobček, Zsolt Čonka, Veljko Đurković, Zoltán Varga
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2026-08-01
Serija:	Solar
Teme:	photovoltaic modules infrared thermography UAV inspection relative-intensity anomaly screening thermal anomaly screening support vector machine
Online dostop:	https://www.mdpi.com/2673-9941/6/4/49
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