Precision-Driven Semantic Segmentation of Pipe Gallery Diseases Using PipeU-NetX: A Depthwise Separable Convolution Approach

Precision-Driven Semantic Segmentation of Pipe Gallery Diseases Using PipeU-NetX: A Depthwise Separable Convolution Approach

Aiming at the problems of high labor cost, low detection efficiency, and insufficient detection accuracy of traditional pipe gallery disease detection methods, this paper proposes a pipe gallery disease segmentation model, PipeU-NetX, based on deep learning technology. By introducing the innovative...

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Bibliographic Details
Main Authors: Wenbin Song, Hanqian Wu, Chunlin Pu
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Computation
Subjects:
pipe gallery disease detection
deep learning
image segmentation
feature extraction
feature fusion
Online Access:https://www.mdpi.com/2079-3197/13/6/143
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