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Multi-class classification method for steel surface defects with feature noise

https://doi.org/10.1007/s42243-020-00501-1
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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/bf00994018openalex-snapshot
Support-Vector Networks
inferredcites →https://doi.org/10.1007/s00521-012-1306-6openalex-snapshot
Twin support vector hypersphere (TSVH) classifier for pattern recognition
inferredcites →https://doi.org/10.1007/s10489-007-0101-zopenalex-snapshot
A new maximal-margin spherical-structured multi-class support vector machine
inferredcites →https://doi.org/10.1007/s10921-016-0370-8openalex-snapshot
A Non-Invasive Technique for Online Defect Detection on Steel Strip Surfaces
inferredcites →https://doi.org/10.1007/s11042-012-1248-0openalex-snapshot
Classification of defects in steel strip surface based on multiclass support vector machine
inferredcites →https://doi.org/10.1016/j.chemolab.2017.10.020openalex-snapshot
Steel surface defects recognition based on multi-type statistical features and enhanced twin support vector machine
inferredcites →https://doi.org/10.1016/j.chemolab.2018.03.014openalex-snapshot
Multi-class classification method using twin support vector machines with multi-information for steel surface defects
inferredcites →https://doi.org/10.1016/j.ins.2012.09.009openalex-snapshot
A twin-hypersphere support vector machine classifier and the fast learning algorithm
inferredcites →https://doi.org/10.1016/j.neucom.2015.05.134openalex-snapshot
Surface defect classification in large-scale strip steel image collection via hybrid chromosome genetic algorithm
inferredcites →https://doi.org/10.1016/s0963-8695(96)00045-xopenalex-snapshot
Optimization of the recognition of defects in flat steel products with the cost matrices theory
inferredcites →https://doi.org/10.1023/b:mach.0000008084.60811.49openalex-snapshot
Support Vector Data Description
inferredcites →https://doi.org/10.1109/tcyb.2016.2551735openalex-snapshot
Maximum Margin of Twin Spheres Support Vector Machine for Imbalanced Data Classification
inferredcites →https://doi.org/10.1109/tip.2010.2047906openalex-snapshot
Switching Bilateral Filter With a Texture/Noise Detector for Universal Noise Removal
inferredcites →https://doi.org/10.1109/tnn.2006.872343openalex-snapshot
Binary tree of SVM: a new fast multiclass training and classification algorithm
inferredcites →https://doi.org/10.1109/tpami.2007.1068openalex-snapshot
Twin Support Vector Machines for Pattern Classification
inferredcites →https://doi.org/10.1109/tpami.2013.178openalex-snapshot
Support Vector Machine Classifier With Pinball Loss
inferredcites →https://doi.org/10.1155/2017/4257273openalex-snapshot
Strip Surface Defects Recognition Based on PSO‐RS&SOCP‐SVM Algorithm
inferredcites →https://doi.org/10.1186/s13640-017-0197-yopenalex-snapshot
An evolutionary classifier for steel surface defects with small sample set
inferredcites →https://doi.org/10.1364/ao.54.009823openalex-snapshot
Surface defect detection method for glass substrate using improved Otsu segmentation
inferredcites →https://doi.org/10.2355/isijinternational.54.119openalex-snapshot
Strip Steel Surface Defect Classification Method Based on Enhanced Twin Support Vector Machine
inferredcites →https://doi.org/10.2355/isijinternational.54.1638openalex-snapshot
Strip Steel Surface Defect Recognition Based on Novel Feature Extraction and Enhanced Least Squares Twin Support Vector Machine
inferredcites →https://doi.org/10.2355/isijinternational.55.207openalex-snapshot
A Fast Detection Method for Region of Defect on Strip Steel Surface
inferredcites →https://doi.org/10.3390/met7080311openalex-snapshot
An Algorithm for Surface Defect Identification of Steel Plates Based on Genetic Algorithm and Extreme Learning Machine

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.4463275openalex-extracted
Twin Margin Distribution Machine with Equality Constraints for Pattern Classification
inferred← citeshttps://doi.org/10.1007/s11227-026-08590-7openalex-snapshot
Mamba-HCIM: a lightweight steel plate surface defect detector via spatial-frequency dual enhancement
inferred← citeshttps://doi.org/10.1007/s42243-023-01059-4openalex-snapshot
DLF-YOLOF: an improved YOLOF-based surface defect detection for steel plate
inferred← citeshttps://doi.org/10.1109/icarm58088.2023.10218864openalex-snapshot
Surface Defect Detection for Die Castings Based on the Improved YOLOv5 Method
inferred← citeshttps://doi.org/10.21203/rs.3.rs-3699994/v1openalex-snapshot
Twin support vector machine with two margin hyperplanes and weighted linear loss
inferred← citeshttps://doi.org/10.3390/a16110516openalex-snapshot
Research on a Classification Method for Strip Steel Surface Defects Based on Knowledge Distillation and a Self-Adaptive Residual Shrinkage Network
inferred← citeshttps://doi.org/10.3390/app16115353openalex-snapshot
RT-DETR-Based Small-Sample Defect Detection for Solar Vacuum Glass Collector Tubes
inferred← citeshttps://doi.org/10.3390/jsan10040073openalex-snapshot
Impact of Image Compression on the Performance of Steel Surface Defect Classification with a CNN
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