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A Real-Time Steel Surface Defect Detection Approach With High Accuracy
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/srin.201600068openalex-snapshot
An End‐to‐End Steel Strip Surface Defects Recognition System Based on Convolutional Neural Networks
inferredcites →https://doi.org/10.1007/978-3-030-55180-3_37openalex-snapshot
Surface Defect Detection Using YOLO Network
inferredcites →https://doi.org/10.1007/978-3-662-54345-0_3openalex-snapshot
Invited Talk: U-Net Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/s11263-019-01204-1openalex-snapshot
CornerNet: Detecting Objects as Paired Keypoints
inferredcites →https://doi.org/10.1016/j.apsusc.2013.09.002openalex-snapshot
A noise robust method based on completed local binary patterns for hot-rolled steel strip surface defects
inferredcites →https://doi.org/10.1016/j.eswa.2010.11.030openalex-snapshot
A vision inspection system for the surface defects of strongly reflected metal based on multi-class SVM
inferredcites →https://doi.org/10.1016/j.ifacol.2018.09.412openalex-snapshot
Real-time Detection of Steel Strip Surface Defects Based on Improved YOLO Detection Network
inferredcites →https://doi.org/10.1016/j.imavis.2015.01.001openalex-snapshot
Application of Shearlet transform to classification of surface defects for metals
inferredcites →https://doi.org/10.1016/j.measurement.2021.109454openalex-snapshot
Development of a YOLO-V3-based model for detecting defects on steel strip surface
inferredcites →https://doi.org/10.1016/j.optlaseng.2019.01.011openalex-snapshot
Surface defect classification of steels with a new semi-supervised learning method
inferredcites →https://doi.org/10.1016/j.optlaseng.2019.06.020openalex-snapshot
Semi-supervised defect classification of steel surface based on multi-training and generative adversarial network
inferredcites →https://doi.org/10.1038/s41598-018-20037-5openalex-snapshot
Advanced Steel Microstructural Classification by Deep Learning Methods
inferredcites →https://doi.org/10.1109/access.2019.2898215openalex-snapshot
Surface Defect Classification for Hot-Rolled Steel Strips by Selectively Dominant Local Binary Patterns
inferredcites →https://doi.org/10.1109/cac48633.2019.8997452openalex-snapshot
Research of Surface Defect Detection Method of Hot Rolled Strip Steel Based on Generative Adversarial Network
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.634openalex-snapshot
Aggregated Residual Transformations for Deep Neural Networks
inferredcites →https://doi.org/10.1109/cvpr.2019.00091openalex-snapshot
Libra R-CNN: Towards Balanced Learning for Object Detection
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00978openalex-snapshot
Bridging the Gap Between Anchor-Based and Anchor-Free Detection via Adaptive Training Sample Selection
inferredcites →https://doi.org/10.1109/iccv.2017.324openalex-snapshot
Focal Loss for Dense Object Detection
inferredcites →https://doi.org/10.1109/iccv.2019.00972openalex-snapshot
FCOS: Fully Convolutional One-Stage Object Detection
inferredcites →https://doi.org/10.1109/mic.2012.6273398openalex-snapshot
The research on defect recognition method for rail magnetic flux leakage detecting
inferredcites →https://doi.org/10.1109/tii.2018.2887145openalex-snapshot
A Simple Guidance Template-Based Defect Detection Method for Strip Steel Surfaces
inferredcites →https://doi.org/10.1109/tii.2019.2958826openalex-snapshot
PGA-Net: Pyramid Feature Fusion and Global Context Attention Network for Automated Surface Defect Detection
inferredcites →https://doi.org/10.1109/tim.2017.2712838openalex-snapshot
Steel Surface Defect Detection Using a New Haar–Weibull-Variance Model in Unsupervised Manner
inferredcites →https://doi.org/10.1109/tim.2018.2795178openalex-snapshot
An Unsupervised-Learning-Based Approach for Automated Defect Inspection on Textured Surfaces
inferredcites →https://doi.org/10.1109/tim.2018.2852918openalex-snapshot
Generalized Completed Local Binary Patterns for Time-Efficient Steel Surface Defect Classification
inferredcites →https://doi.org/10.1109/tim.2019.2915404openalex-snapshot
An End-to-End Steel Surface Defect Detection Approach via Fusing Multiple Hierarchical Features
inferredcites →https://doi.org/10.1109/tpami.2015.2389824openalex-snapshot
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
inferredcites →https://doi.org/10.1109/tpami.2016.2577031openalex-snapshot
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
inferredcites →https://doi.org/10.1109/tpami.2019.2956516openalex-snapshot
Cascade R-CNN: High Quality Object Detection and Instance Segmentation
inferredcites →https://doi.org/10.1155/2021/5592878openalex-snapshot
A New Steel Defect Detection Algorithm Based on Deep Learning
inferredcites →https://doi.org/10.1609/aaai.v33i01.33019259openalex-snapshot
M2Det: A Single-Shot Object Detector Based on Multi-Level Feature Pyramid Network
inferredcites →https://doi.org/10.2355/isijinternational.isijint-2020-451openalex-snapshot
Surface Defects Classification of Hot Rolled Strip Based on Improved Convolutional Neural Network
inferredcites →https://doi.org/10.3390/met10060846openalex-snapshot
Steel Surface Defect Classification Using Deep Residual Neural Network
inferredcites →https://doi.org/10.3390/met11030388openalex-snapshot
Automatic Detection and Classification of Steel Surface Defect Using Deep Convolutional Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4469855openalex-extracted
Steel Surface Defect Classification Based on Legendre Multiwavelet Transform and SVM
inferred← citeshttps://doi.org/10.2139/ssrn.4524941openalex-extracted
Steel Surface Defect Classification Based on Legendre Multiwavelet Transform and SVM
inferred← citeshttps://doi.org/10.1007/978-981-97-0827-7_16openalex-snapshot
Multi-scale Texture Network for Industrial Surface Defect Detection
inferred← citeshttps://doi.org/10.1007/s00371-023-02980-1openalex-snapshot
A dual-structure attention-based multi-level feature fusion network for automatic surface defect detection
inferred← citeshttps://doi.org/10.1007/s00500-026-11392-xopenalex-snapshot
Improved Mask R-CNN for defect detection in aluminum alloy rims
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A survey of real-time surface defect inspection methods based on deep learning
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Few-shot defect detection using feature enhancement and image generation for manufacturing quality inspection
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Human–machine knowledge hybrid augmentation method for surface defect detection based few-data learning
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A Highly Efficient and Lightweight Detection Method for Steel Surface Defect
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A Lightweight RT-DETR Model for Metal Surface Defect Detection Using Multi-Scale Network and Additive Attention Mechanism
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An efficient model for metal surface defect detection based on attention mechanism and multi-scale feature
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RFAConv-CBM-ViT: enhanced vision transformer for metal surface defect detection
inferred← citeshttps://doi.org/10.1007/s11227-025-07036-wopenalex-snapshot
Multi-scale and dynamic snake convolution-based YOLOv9 for steel surface defect detection
inferred← citeshttps://doi.org/10.1007/s11263-025-02718-7openalex-snapshot
A Novel Dataset and Lightweight Distillation Baseline for Highlight Transparent Object Detection
inferred← citeshttps://doi.org/10.1007/s12652-025-05034-7openalex-snapshot
Steel surface defect detection based on lightweight network with attention feature fusion and multi-scale detection head
inferred← citeshttps://doi.org/10.1007/s13369-024-09352-4openalex-snapshot
High-Frequency Dual-Branch Network for Steel Small Defect Detection
inferred← citeshttps://doi.org/10.1016/j.engappai.2023.106474openalex-snapshot
SMINet:Semantics-aware multi-level feature interaction network for surface defect detection
inferred← citeshttps://doi.org/10.1038/s41598-024-57990-3openalex-snapshot
Surface defect detection of hot rolled steel based on multi-scale feature fusion and attention mechanism residual block
inferred← citeshttps://doi.org/10.1038/s41598-025-94164-1openalex-snapshot
Online high speed detection method for end face quality of cored filter rods under complex conditions
inferred← citeshttps://doi.org/10.1049/cit2.12407openalex-snapshot
A Fast Surface-Defect Detection Method Based on Dense-Yolo Network
inferred← citeshttps://doi.org/10.1061/jitse4.iseng-2747openalex-snapshot
Real-Time Rust Segmentation on Steel Surface Using a Lightweight Transformer Deep Learning Model
inferred← citeshttps://doi.org/10.1080/00207543.2025.2605085openalex-snapshot
Integrating explainable artificial intelligence with vision-based surface defect detection systems for realizing zero-defect manufacturing
inferred← citeshttps://doi.org/10.1080/10589759.2025.2524604openalex-snapshot
EN-YOLO: a featured-enhanced model for precise hot rolled steel surface defect detection
inferred← citeshttps://doi.org/10.1109/access.2023.3271748openalex-snapshot
Deep Learning for Automatic Vision-Based Recognition of Industrial Surface Defects: A Survey
inferred← citeshttps://doi.org/10.1109/access.2024.3349628openalex-snapshot
A Novel Feature Extraction Method Based on Legendre Multi-Wavelet Transform and Auto-Encoder for Steel Surface Defect Classification
inferred← citeshttps://doi.org/10.1109/access.2024.3378999openalex-snapshot
LCG-YOLO: A Real-Time Surface Defect Detection Method for Metal Components
inferred← citeshttps://doi.org/10.1109/access.2024.3391353openalex-snapshot
EC-YOLO: Effectual Detection Model for Steel Strip Surface Defects Based on YOLO-V5
inferred← citeshttps://doi.org/10.1109/access.2026.3737532openalex-snapshot
DSA-YOLO: Coupling Spectral and Spatial Cues for Lightweight Strip Steel Surface Defect Detection
inferred← citeshttps://doi.org/10.1109/aetcse69203.2026.11504445openalex-snapshot
Modified VMamba-UNet for Pipeline Weld Defect Detection
inferred← citeshttps://doi.org/10.1109/cac59555.2023.10451921openalex-snapshot
GCE-YOLOv5s Based Surface Defect Detection Algorithm for Strip Steel
inferred← citeshttps://doi.org/10.1109/eeiss62553.2024.00012openalex-snapshot
Surface Tiny Defect Detection Based on Gaussian Distribution Modeling and Adaptive Feature Fusion
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Improvement of Low-Contrast Objective Detecting Capability for YOLOv5 Based on Receptive Field Enhancement and Redundant Feature Reuse
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A New Dual-Branch Network With Global Information for the Surface Defect Detection on Solar PV Wafer
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Application of Improved YOLOv5 Model for Strip Surface Defect Detection
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Enhanced Defect Detection Network: Leveraging Large Kernel and Dynamic Task Interaction for Precise Prediction
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A CAM-Based Weakly Supervised Method for Surface Defect Inspection
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An Anchor-Free Defect Detector for Complex Background Based on Pixelwise Adaptive Multiscale Feature Fusion
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DCAM-Net: A Rapid Detection Network for Strip Steel Surface Defects Based on Deformable Convolution and Attention Mechanism
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AGCA: An Adaptive Graph Channel Attention Module for Steel Surface Defect Detection
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Internal Defect Detection of Overhead Aluminum Conductor Composite Core Transmission Lines With an Inspection Robot and Computer Vision
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Steel Surface Defect Detection via Deformable Convolution and Background Suppression
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KD-LightNet: A Lightweight Network Based on Knowledge Distillation for Industrial Defect Detection
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ETDNet: Efficient Transformer-Based Detection Network for Surface Defect Detection
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CDDNet: Camouflaged Defect Detection Network for Steel Surface
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A-Net: An A-Shape Lightweight Neural Network for Real-Time Surface Defect Segmentation
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Joining Spatial Deformable Convolution and a Dense Feature Pyramid for Surface Defect Detection
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AFF-Net: A Strip Steel Surface Defect Detection Network via Adaptive Focusing Features
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TAANet: A Task-Aware Attention Network for Weak Surface Defect Detection
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STD2: Swin Transformer-Based Defect Detector for Surface Anomaly Detection
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SOKD: A Soft Optimization Knowledge Distillation Scheme for Surface Defects Identification of Hot-Rolled Strip
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Wavelet Texture Descriptor for Steel Surface Defect Classification
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