Defect Classification

Defect classification aims to automatically identify and categorize different types of defects within various systems, from manufacturing processes to infrastructure inspections, primarily using image or signal data. Current research emphasizes improving the accuracy and efficiency of defect classification, particularly in scenarios with limited or imbalanced data, focusing on advanced deep learning architectures like convolutional neural networks (CNNs), diffusion models, and memory-augmented state space models, often incorporating techniques like transfer learning and data augmentation. These advancements have significant implications for enhancing quality control in manufacturing, improving infrastructure maintenance, and accelerating the pace of scientific discovery in materials science and other fields.

Papers

October 14, 2024

Enhancing Apple's Defect Classification: Insights from Visible Spectrum and Narrow Spectral Band Imaging
Omar Coello, Moisés Coronel, Darío Carpio, Boris Vintimilla, Luis Chuquimarca
Convolutional Neural Network DCU Insight AQ Defect Classification Spectral Band

August 1, 2024

May 6, 2024

MemoryMamba: Memory-Augmented State Space Model for Defect Recognition
Qianning Wang, He Hu, Yucheng Zhou
Defect Detection Defect Classification

April 8, 2024

Progressive Alignment with VLM-LLM Feature to Augment Defect Classification for the ASE Dataset
Chih-Chung Hsu, Chia-Ming Lee, Chun-Hung Sun, Kuang-Ming Wu
Large Vision Language Model Defect Classification Progressive Alignment Defect Sample Defect Class

April 4, 2024

DeepFunction: Deep Metric Learning-based Imbalanced Classification for Diagnosing Threaded Pipe Connection Defects using Functional Data
Yukun Xie, Juan Du, Chen Zhang
Deep Metric Learning Functional Data Analysis Defect Classification Defect Sample Pipe Inspection Defect Class Deep Function

November 2, 2023

Overhead Line Defect Recognition Based on Unsupervised Semantic Segmentation
Weixi Wang, Xichen Zhong, Xin Li, Sizhe Li, Xun Ma
Semantic Segmentation Defect Detection Unsupervised Semantic Segmentation Defect Classification

October 26, 2023

Defect Spectrum: A Granular Look of Large-Scale Defect Datasets with Rich Semantics
Shuai Yang, Zhifei Chen, Pengguang Chen, Xi Fang, Shu Liu, Yingcong Chen
Defect Detection Multi Granularity Defect Classification Defect Datasets Defect Inspection

October 16, 2023

Observational and Experimental Insights into Machine Learning-Based Defect Classification in Wafers
Kamal Taha
Machine Learning New Machine Defect Classification Wafer Defect

September 22, 2023

Decision Fusion Network with Perception Fine-tuning for Defect Classification
Xiaoheng Jiang, Shilong Tian, Zhiwen Zhu, Yang Lu, Hao Liu, Li Chen, Shupan Li, Mingliang Xu
Feature Importance Defect Classification Decision Level Fusion Surface Inspection

July 21, 2023

DEFTri: A Few-Shot Label Fused Contextual Representation Learning For Product Defect Triage in e-Commerce
Ipsita Mohanty
E Commerce Text Embeddings Contextual Representation Pre Trained BERT Defect Classification Bug Triaging

July 14, 2023

Defect Classification in Additive Manufacturing Using CNN-Based Vision Processing
Xiao Liu, Alessandra Mileo, Alan F. Smeaton
Convolutional Neural Network Computer Vision Image Processing Image Datasets Defect Classification

June 2, 2023

GANs and alternative methods of synthetic noise generation for domain adaption of defect classification of Non-destructive ultrasonic testing
Shaun McKnight, S. Gareth Pierce, Ehsan Mohseni, Christopher MacKinnon, Charles MacLeod, Tom OHare, Charalampos Loukas
GAN Model Synthetic Data Generation Synthetic Datasets Defect Classification Domain Adaption Scientific Image Composite Material Noise Generation Ultrasonic Non Destructive Testing

December 1, 2022

Semiconductor Defect Pattern Classification by Self-Proliferation-and-Attention Neural Network
YuanFu Yang, Min Sun
Defect Detection Defect Classification

November 3, 2022

Deep Learning based Defect classification and detection in SEM images: A Mask R-CNN approach
Bappaditya Dey, Enrique Dehaerne, Kasem Khalil, Sandip Halder, Philippe Leray, Magdy A. Bayoumi
Deep Learning Data Detection SEM Image Defect Classification Defect Segmentation Mask R CNN Semiconductor Defect Inspection Defect Class

September 6, 2022

Automated Defect Recognition of Castings defects using Neural Networks
Alberto García-Pérez, María José Gómez-Silva, Arturo de la Escalera
Neural Network Convolutional Neural Network X Ray Defect Detection Defect Classification Surface Defect

June 20, 2022

Deep Learning-Based Defect Classification and Detection in SEM Images
Bappaditya Deya, Dipam Goswamif, Sandip Haldera, Kasem Khalilb, Philippe Leraya, Magdy A. Bayoumi
Data Detection SEM Image Defect Classification Defect Class

March 20, 2022

Deep Learning based Intelligent Coin-tap Test for Defect Recognition
Hongyu Li, Peng Jiang, Tiejun Wang
Deep Learning Convolutional Neural Network CNN Model Non Destructive Defect Classification

March 16, 2022

A Continual Learning Framework for Adaptive Defect Classification and Inspection
Wenbo Sun, Raed Al Kontar, Judy Jin, Tzyy-Shuh Chang
Image Classification Defect Detection Visual Inspection Surface Defect Detection COntinual Learning Framework Quality Inspection Defect Classification

February 12, 2022

The Impact of Using Regression Models to Build Defect Classifiers
Gopi Krishnan Rajbahadur, Shaowei Wang, Yasutaka Kamei, Ahmed E. Hassan
Global Impact Regression Model Defect Classification

Defect Classification

Papers

Enhancing Apple's Defect Classification: Insights from Visible Spectrum and Narrow Spectral Band Imaging

Multi-label Sewer Pipe Defect Recognition with Mask Attention Feature Enhancement and Label Correlation Learning

Few-shot Defect Image Generation based on Consistency Modeling

MemoryMamba: Memory-Augmented State Space Model for Defect Recognition

Progressive Alignment with VLM-LLM Feature to Augment Defect Classification for the ASE Dataset

DeepFunction: Deep Metric Learning-based Imbalanced Classification for Diagnosing Threaded Pipe Connection Defects using Functional Data

Overhead Line Defect Recognition Based on Unsupervised Semantic Segmentation

Defect Spectrum: A Granular Look of Large-Scale Defect Datasets with Rich Semantics

Observational and Experimental Insights into Machine Learning-Based Defect Classification in Wafers

Decision Fusion Network with Perception Fine-tuning for Defect Classification

DEFTri: A Few-Shot Label Fused Contextual Representation Learning For Product Defect Triage in e-Commerce

Defect Classification in Additive Manufacturing Using CNN-Based Vision Processing

GANs and alternative methods of synthetic noise generation for domain adaption of defect classification of Non-destructive ultrasonic testing

Semiconductor Defect Pattern Classification by Self-Proliferation-and-Attention Neural Network

Deep Learning based Defect classification and detection in SEM images: A Mask R-CNN approach

Automated Defect Recognition of Castings defects using Neural Networks

Deep Learning-Based Defect Classification and Detection in SEM Images

Deep Learning based Intelligent Coin-tap Test for Defect Recognition

A Continual Learning Framework for Adaptive Defect Classification and Inspection

The Impact of Using Regression Models to Build Defect Classifiers