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A Generalized Framework for Critical Heat Flux Detection Using Unsupervised Image-to-Image Translation

Firas Al-HindawiTejaswi SooribHan Hu ...+3 Ying Sun
Dec 2022
摘要
This work proposes a framework developed to generalize Critical Heat Flux(CHF) detection classification models using an Unsupervised Image-to-Image(UI2I) translation model. The framework enables a typical classification modelthat was trained and tested on boiling images from domain A to predict boilingimages coming from domain B that was never seen by the classification model.This is done by using the UI2I model to transform the domain B images to looklike domain A images that the classification model is familiar with. AlthoughCNN was used as the classification model and Fixed-Point GAN (FP-GAN) was usedas the UI2I model, the framework is model agnostic. Meaning, that the frameworkcan generalize any image classification model type, making it applicable to avariety of similar applications and not limited to the boiling crisis detectionproblem. It also means that the more the UI2I models advance, the better theperformance of the framework.
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