Problem
Research questions and friction points this paper is trying to address.
Visual Question Answering
nondestructive evaluation
image analysis
A Visual Question Answering Model to Automate Nondestructive Evaluation Image Analysis
๐ค AI Summary
็ ็ฉถๆๅบไบไธ็ง่ง่ง้ฎ็ญๆจกๅ๏ผ็จไบ้็ ดๅๆงๆฃๆตๅพๅๅๆ๏ผ้่ฟๆทฑๅบฆๅญฆไน ๅ่ช็ถ่ฏญ่จๅค็ๆๆฏๆ้ซๆฃๆตๆ็ๅๅ็กฎๆงใ
๐ 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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Visual Question Answering
Nondestructive Evaluation
Deep Learning
Natural Language Processing
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