Deep Learning-Based Multi-Scale Bubble Detection and Feature Analysis

The morphological characteristics of bubbles in gas–liquid two-phase flow serve as an important basis for the study of heat and mass transfer as well as the design of chemical reaction equipment. These characteristics are widely applied in industrial fields such as petroleum, chemical engineering, e...

وصف كامل

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Lichun Bai (6684683) (author)
مؤلفون آخرون:	Xuan Wang (55634) (author), Sen Lin (182597) (author), Zishu Chai (21495952) (author), Ronghui Zhao (14325732) (author)
منشور في:	2025
الموضوعات:	Genetics Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified phase flow serve global contextual information enhanced algorithm attains efficient complete intersection integrates multiscale features capture multiscale features reduce feature redundancy good detection performance chemical reaction equipment scale bubble detection bubble morphological parameters channel reconstruction convolution bubble sizes feature analysis detection process chemical engineering detection capability multiscale bubbles widely applied speed camera paper proposes neck network morphological characteristics missed detections mass transfer loss function large variation industrial fields important basis fully demonstrating finely adjust false detections experimental findings environmental protection dense distribution deep learning bounding boxes backbone network
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