Year: 2025
Type: conference-paper
Abstract: This study introduces a Visual Question Answering (VQA) model designed specifically for nondestructive evaluation (NDE) 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.
Authors: MEHRDAD S. DIZAJI, HODA AZARI
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
Funder: Federal Highway Administration
OpenAlex ID: W4415216821
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