Surface Defect Classification for Hot-Rolled Steel Strips by Selectively Dominant Local Binary Patterns

Multiresolution gray-scale and rotation invariant texture classification with local binary patterns

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Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions

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Dominant Local Binary Patterns for Texture Classification

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Median Robust Extended Local Binary Pattern for Texture Classification

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Local binary features for texture classification: Taxonomy and experimental study

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Automatic Defect Detection on Hot-Rolled Flat Steel Products

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Pairwise Rotation Invariant Co-Occurrence Local Binary Pattern

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Completed Local Binary Count for Rotation Invariant Texture Classification

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Remote Sensing Scene Classification by Unsupervised Representation Learning

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Noise-Resistant Local Binary Pattern With an Embedded Error-Correction Mechanism

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Discriminative features for texture description

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Semi-Supervised Multitask Learning for Scene Recognition

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Generalized Completed Local Binary Patterns for Time-Efficient Steel Surface Defect Classification

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Steel Surface Defect Detection Using a New Haar–Weibull-Variance Model in Unsupervised Manner

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Improving Automatic Detection of Defects in Castings by Applying Wavelet Technique

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A cost-effective and automatic surface defect inspection system for hot-rolled flat steel

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Detection and classification of surface defects of gun barrels using computer vision and machine learning

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Combining LBP Difference and Feature Correlation for Texture Description

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Noise tolerant local binary pattern operator for efficient texture analysis

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Ambiguous Surface Defect Image Classification of AMOLED Displays in Smartphones

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Robust Visual Detection–Learning–Tracking Framework for Autonomous Aerial Refueling of UAVs

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An intelligent system for quality measurement of Golden Bleached raisins using two comparative machine learning algorithms

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Adaptive surface inspection via interactive evolution

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A fast method of steel surface defect detection using decision trees applied to LBP based features

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Application of multi-scale feature extraction to surface defect classification of hot-rolled steels

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Multi-scale Joint Encoding of Local Binary Patterns for Texture and Material Classification

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Pretest Gap Mura on TFT LCDs Using the Optical Interference Pattern Sensing Method and Neural Network Classification

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Discriminant Analysis for Fast Multiclass Data Classification Through Regularized Kernel Function Approximation

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Vibrations in Steel Strips: Effects on Flatness Measurement and Filtering

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Application of Segmented 2-D Probabilistic Occupancy Maps for Robot Sensing and Navigation

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Application of texture analysis method for mammogram density classification

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A three-dimensional inspection system for high temperature steel product surface sample height using stereo vision and blue encoded patterns

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A texture-based rolling bearing fault diagnosis scheme using adaptive optimal kernel time frequency representation and uniform local binary patterns

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Automated Visual Defect Detection for Flat Steel Surface: A Survey

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Recent advances in surface defect inspection of industrial products using deep learning techniques

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Review of surface defect detection of steel products based on machine vision

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Steel Surface Defect Recognition: A Survey

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Research Progress of Automated Visual Surface Defect Detection for Industrial Metal Planar Materials

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X-SDD: A New Benchmark for Hot Rolled Steel Strip Surface Defects Detection

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Automated Visual Defect Classification for Flat Steel Surface: A Survey

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Surface Defect Detection of Steel Strips Based on Anchor-Free Network With Channel Attention and Bidirectional Feature Fusion

Yu, J., Cheng, X., & Li, Q. (2021) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2021.3136183 · Cited by 124 · see citing works

Surface defect detection of steel strips based on classification priority YOLOv3-dense network

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SSA-YOLO: An Improved YOLO for Hot-Rolled Strip Steel Surface Defect Detection

Huang, X., Zhu, J., & Huo, Y. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3488136 · Cited by 98 · see citing works

A ResNet50-Based Method for Classifying Surface Defects in Hot-Rolled Strip Steel

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Cross Position Aggregation Network for Few-Shot Strip Steel Surface Defect Segmentation

Feng, H., Song, K., Cui, W., Zhang, Y., & Yan, Y. (2023) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2023.3246519 · Cited by 84 · see citing works

A Real-Time Steel Surface Defect Detection Approach With High Accuracy

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A Generic Semi-Supervised Deep Learning-Based Approach for Automated Surface Inspection

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A Survey of Vision-Based Methods for Surface Defects’ Detection and Classification in Steel Products

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Fabric Defect Detection With Deep Learning and False Negative Reduction

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Multiple channels local binary pattern for color texture representation and classification

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Deep Learning Approaches to Image Texture Analysis in Material Processing

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CABF-YOLO: a precise and efficient deep learning method for defect detection on strip steel surface

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Using global information to refine local patterns for texture representation and classification

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Deep learning-based automated steel surface defect segmentation: a comparative experimental study

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A Lightweight Network for Defect Detection in Nickel-Plated Punched Steel Strip Images

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Scale-selective and noise-robust extended local binary pattern for texture classification

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Research on Surface Defect Detection of Strip Steel Based on Improved YOLOv7

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Unsupervised defect detection with patch-aware mutual reasoning network in image data

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Surface Defect Classification of Steel Strip with Few Samples Based on Dual‐Stream Neural Network

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A multi-channel framework based Local Binary Pattern with two novel local feature descriptors for texture classification

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Method for automatic railway track surface defect classification and evaluation using a laser‐based 3D model

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Explainable efficient and optimized feature fusion network for surface defect detection

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Steel Strip Quality Assurance With YOLOV7-CSF: A Coordinate Attention and SIoU Fusion Approach

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An End-to-End Steel Surface Classification Approach Based on EDCGAN and MobileNet V2

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AFFNet: An Attention-Based Feature-Fused Network for Surface Defect Segmentation

Chen, X., Fu, C., Tie, M., Sham, C., & Ma, H. (2023) · Applied Sciences · doi:10.3390/app13116428 · Cited by 17 · see citing works

TSEDNet:Task-specific encoder–decoder network for surface defects of strip steel

Guo, Y., Wei, J., & Feng, X. (2024) · Measurement · doi:10.1016/j.measurement.2024.115438 · Cited by 17 · see citing works

Legendre multiwavelet-based feature attention guidance lightweight network for accurate steel surface defect classification

Zheng, X., Liu, W., & Huang, Y. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.112179 · Cited by 15 · see citing works

AEDN-YOLO: an efficient one-stage detection network for strip steel surface defects

Wei, M., Chen, B., Liu, J., Yuan, N., Liu, J., & Ji, Z. (2024) · Engineering Research Express · doi:10.1088/2631-8695/ad681d · Cited by 15 · see citing works

Binary Gabor pattern (BGP) descriptor and principal component analysis (PCA) for steel surface defects classification

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Automatic Detection and Quantification of Hot-Rolled Steel Surface Defects Using Deep Learning

Liu, Z., Zeng, Z., Li, J., & Teng, S. (2022) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-022-07567-x · Cited by 15 · see citing works

ADDet: An Efficient Multiscale Perceptual Enhancement Network for Aluminum Defect Detection

Zhu, J., Pang, Q., Li, S., Tian, S., Li, J., & Li, Y. (2023) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2023.3343789 · Cited by 14 · see citing works

A lightweight convolutional neural network for surface defect detection in strip steel

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Flexible and Diverse Contrastive Learning for Steel Surface Defect Recognition With Few Labeled Samples

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Enhancing Metal Surface Defect Recognition Through Image Patching and Synthetic Defect Generation

Mustafaev, B., Kim, S., & Kim, E. S. (2023) · IEEE Access · doi:10.1109/access.2023.3322734 · Cited by 11 · see citing works

Resformer-Unet: A U-shaped Framework Combining ResNet and Transformer for Segmentation of Strip Steel Surface Defects

Lu, K., Wang, W., Pan, X., Zhou, Y., Chen, Z., Zhao, Y., & Wang, B. (2023) · ISIJ International · doi:10.2355/isijinternational.isijint-2023-222 · Cited by 10 · see citing works

Rain-Like Layer Removal From Hot-Rolled Steel Strip Based on Attentive Dual Residual Generative Adversarial Network

Luo, Q., He, H., Liu, K., Yang, C., Sílven, O., & Liu, L. (2023) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2023.3265761 · Cited by 9 · see citing works

Spiking ViT: spiking neural networks with transformer—attention for steel surface defect classification

Gong, L., Dong, H., Zhang, X., Cheng, X., Ye, F., Guo, L., & Ge, Z. (2024) · Journal of Electronic Imaging · doi:10.1117/1.jei.33.3.033001 · Cited by 9 · see citing works

High Speed Partial Pattern Classification System Using a CAM-Based LBP Histogram on FPGA

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Directional Neighborhood Topologies Based Multi-Scale Quinary Pattern for Texture Classification

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An Artificial-Intelligence-Driven Predictive Model for Surface Defect Detections in Medical MEMS

Amini, A., Kanfoud, J., & Gan, T. (2021) · Sensors · doi:10.3390/s21186141 · Cited by 9 · see citing works

Improving the Performance of the Single Shot Multibox Detector for Steel Surface Defects with Context Fusion and Feature Refinement

Li, Y., He, L., Zhang, M., Cheng, Z., Liu, W., & Wu, Z. (2023) · Electronics · doi:10.3390/electronics12112440 · Cited by 10 · see citing works

Triple-attentions based salient object detector for strip steel surface defects

Zhang, L., Li, X., Sun, Y., & Guo, H. (2025) · Scientific Reports · doi:10.1038/s41598-025-86353-9 · Cited by 8 · see citing works

Defect Detection and Classification of Strip Steel Based on Improved VIT Model

Xing, L., Li, T., Fan, H., & Zhu, H. (2022) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-03948-5_26 · Cited by 7 · see citing works

FCCNet: Surface Defects Identification of Hot Rolled Strip Based on Lightweight Convolutional Neural Network

Lu, K., Wang, W., Feng, X., Zhou, Y., Chen, Z., Zhao, Y., & Wang, B. (2023) · ISIJ International · doi:10.2355/isijinternational.isijint-2023-182 · Cited by 6 · see citing works

Surface Defect Classification of Steels Based on Ensemble of Extreme Learning Machines

Liu, Y., Jin, Y., & Ma, H. (2019) · WRC Symposium on Advanced Robotics and Automation (WRC SARA) · doi:10.1109/wrc-sara.2019.8931807 · Cited by 6 · see citing works

A novel prior knowledge-based and texture-enhanced network for few-shot industrial defect segmentation

Liu, X., Wu, Q., Cheng, Y., & Wen, G. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.112408 · Cited by 5 · see citing works

A nested autoencoder approach to automated defect inspection on textured surfaces

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Content-Based Image Retrieval for Surface Defects of Hot Rolled Steel Strip Using Wavelet-Based LBP

Boudani, F. Z., Nacereddine, N., & Laiche, N. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-89691-1_39 · Cited by 5 · see citing works

Texture Features Extraction Using Wavelet-Based CLBP for Surface Defects Retrieval of Hot Rolled Steel Strip

Boudani, F. Z., Nacereddine, N., & Laiche, N. (2023) · International Conference on Systems and Control (ICSC) · doi:10.1109/icsc58660.2023.10449740 · Cited by 4 · see citing works

Slim-YOLOv8: A fast and accurate algorithm for surface defect detection of steel strips

Zhao, J., Liu, S., Tao, H., & Liu, W. (2024) · Ironmaking & Steelmaking Processes Products and Applications · doi:10.1177/03019233241266717 · Cited by 3 · see citing works

Using optical flow algorithm based on dynamic illumination mode to examine defects on highly reflective turbine blade surface

Shang, X., Song, W., Chen, Z., & Zhang, C. (2022) · IET Image Processing · doi:10.1049/ipr2.12608 · Cited by 2 · see citing works

Complementary feature fusion network for few-shot segmentation of steel surface defect

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Study on Analysis of Defect Identification Methods in Manufacturing Industry

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Microsurface Defect Recognition via Microlaser Line Projection and Affine Moment Invariants

Rodríguez, J. A. M. (2025) · Coatings · doi:10.3390/coatings15040385 · Cited by 1 · see citing works

Evaluation of computer vision techniques for quality inspection in casting manufacturing process

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DEGRNet: An innovative dual-branch edge-based graph reasoning network for the few-shot segmentation of industrial surface defects

Wu, Q., Liu, X., Wen, G., Liao, G., & Shi, T. (2025) · Frontiers of Mechanical Engineering · doi:10.1007/s11465-025-0863-1 · Cited by 1 · see citing works

A Lightweight Model for Hot-Rolled Steel Strip Surface Defect Recognition

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Steel surface defect classification approach using an All-optical Neuron-based SNN with attention mechanism

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SOKD: A Soft Optimization Knowledge Distillation Scheme for Surface Defects Identification of Hot-Rolled Strip

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Construction of an Energy Saving Model Based on FA and Its Applications for Detection of Battery Power Consumption

Wu, Q., Ma, Z., Chen, W., Li, C., & Hu, C. (2020) · IEEE Access · doi:10.1109/access.2020.2981371

Defect Detection Method of Steel Coil End Face Based on Gray Integral Projection

Wang, B., Chen, J., & Zhu, L. (2022) · Lecture notes in electrical engineering · doi:10.1007/978-981-19-1309-9_180

Compact and Efficient Feature Representation for Defect in hot rolled strip steel:A postion paper

Su, J., Luo, Q., & Yang, C. (2022) · Asian Control Conference (ASCC) · doi:10.23919/ascc56756.2022.9828012

A fast method for load detection and classification using texture image classification in intelligent transportation systems

Eghbal, N., Anaraki, B. G., & Shami, F. C. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-18445-z

SSDC-Net: An Effective Classification Method of Steel Surface Defects Based on Salient Local Features

Hao, Q., Gan, Q., Liu, Z., Chen, J., Shen, Q., Qian, C., & Liu, Y. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-5588-2_41

Integrating local binary patterns and convolutional neural networks with a balanced gray encoded pooling mechanism

Lai, C.-L., Tseng, L.-S., Chang, C.-H., Chen, Y.-H., & Wu, C. (2025) · Multimedia Tools and Applications · doi:10.1007/s11042-025-20823-0

A Study on a Directional Gradient-Based Defect Detection Method for Plate Heat Exchanger Sheets

Zhi-Bo, D., & Yuan, W. (2025) · Electronics · doi:10.3390/electronics14163206

Super-resolution-guided dense enhancement segmentation network for defect detection of strip steel

Deng, Y., Liu, Y., Li, X., Zhao, F., Yang, H., & Xu, C. (2026) · Engineering Research Express · doi:10.1088/2631-8695/ae4676

DSA-YOLO: Coupling Spectral and Spatial Cues for Lightweight Strip Steel Surface Defect Detection

Cheng, C., & You, Q. (2026) · IEEE Access · doi:10.1109/access.2026.3737532

Generalized Completed Local Binary Patterns for Time-Efficient Steel Surface Defect Classification

Luo, Q., Sun, Y., Li, P., Simpson, O., Tian, L., & He, Y. (2019) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2018.2852918 · Cited by 178 · see citing works

A noise robust method based on completed local binary patterns for hot-rolled steel strip surface defects

Song, K., & Yan, Y. (2013) · Applied Surface Science · doi:10.1016/j.apsusc.2013.09.002 · Cited by 1,026 · see citing works

Binary Gabor pattern (BGP) descriptor and principal component analysis (PCA) for steel surface defects classification

Zaghdoudi, R., Séridi, H., Boudiaf, A., & Ziani, S. (2020) · International Conference on Advanced Aspects of Software Engineering (ICAASE) · doi:10.1109/icaase51408.2020.9380108 · Cited by 16 · see citing works

Online Surface Defect Identification of Cold Rolled Strips Based on Local Binary Pattern and Extreme Learning Machine

Liu, Y., Xu, K., & Wang, D. (2018) · Metals · doi:10.3390/met8030197 · Cited by 39 · see citing works

Study on Surface Defect Classification of Hot-Rolled Strip Based on PSO-SVM

Ye, X., & Xu, S. (2022) · Lecture notes in electrical engineering · doi:10.1007/978-981-19-1309-9_176 · Cited by 4 · see citing works