क्यूआर कोड

ID-MSNet: An Enhanced Multi-Scale Network with Convolutional Attention for Pixel-Level Steel Defect Segmentation

Automated pixel-level detection of steel surface defects is a critical challenge in manufacturing quality control, complicated by the variation in defect size and shape, low contrast with background textures, and the diversity of defect patterns. This paper proposes ID-MSNet, an enhanced version of...

पूर्ण विवरण

में बचाया:
मुख्य लेखकों: Mohammadreza Saberironaghi, Jing Ren, Alireza Saberironaghi
स्वरूप: Artigo
भाषा:Inglês
प्रकाशित: MDPI AG 2026-04-01
श्रृंखला:Algorithms
विषय:
defect detection
surface defect detection
steel defect detection
defect segmentation
UNet3+
attention mechanism
ऑनलाइन पहुंच:https://www.mdpi.com/1999-4893/19/4/294
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