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A Visual Question Answering Model to Automate Nondestructive Evaluation Image Analysis

2026-08-29 19:19:45
Mehrdad Shafiei Dizaji, Hoda Azari
arXiv_CV
             
Abstract

This study introduces a Visual Question Answering model designed specifically for nondestructive evaluation applications. VQA models allow inspectors to interactively query NDE images, asking targeted questions like, Is there a crack or Where is the defect located and receive precise answers from the model. Leveraging deep learning and natural language processing, the developed system integrates image feature extraction (via a ResNet-50 model) and language generation capabilities (via GPT-2) to provide accurate, informative feedback. By enabling direct question-and-answer interactions, this VQA model significantly improves inspection efficiency, reduces potential errors, and enhances usability in practical field scenarios.

Abstract (translated)

URL

https://arxiv.org/abs/2608.29408

PDF

https://arxiv.org/pdf/2608.29408.pdf

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