Papers Defect Detection
“Defect Detection” 태그가 달린 논문 394편 · 필터 해제
RailTrack-DaViT: A Vision Transformer-Based Approach for Automated Railway Track Defect Detection
Railway track defects pose significant safety risks and can lead to accidents, economic losses, and loss of life. Traditional manual inspection methods are either time-consuming, costly, or prone to human error. This pap…
Defect DetectionSuperSimpleNet: Unifying Unsupervised and Supervised Learning for Fast and Reliable Surface Defect Detection
The aim of surface defect detection is to identify and localise abnormal regions on the surfaces of captured objects, a task that's increasingly demanded across various industries. Current approaches frequently fail to f…
Anomaly DetectionDefect DetectionSupervised Defect DetectionFew-shot Defect Image Generation based on Consistency Modeling
Image generation can solve insufficient labeled data issues in defect detection. Most defect generation methods are only trained on a single product without considering the consistencies among multiple products, leading …
Defect DetectionDiversityImage GenerationStatistical Batch-Based Bearing Fault Detection
In the domain of rotating machinery, bearings are vulnerable to different mechanical faults, including ball, inner, and outer race faults. Various techniques can be used in condition-based monitoring, from classical sign…
Defect DetectionFault DetectionYOLO-pdd: A Novel Multi-scale PCB Defect Detection Method Using Deep Representations with Sequential Images
With the rapid growth of the PCB manufacturing industry, there is an increasing demand for computer vision inspection to detect defects during production. Improving the accuracy and generalization of PCB defect detection…
Defect Detectionobject-detectionObject DetectionGDDS: A Single Domain Generalized Defect Detection Frame of Open World Scenario using Gather and Distribute Domain-shift Suppression Network
Efficient and intelligent surface defect detection of photovoltaic modules is crucial for improving the quality of photovoltaic modules and ensuring the reliable operation of large-scale infrastructure. However, the scen…
Defect DetectionDomain GeneralizationIn-Situ Infrared Camera Monitoring for Defect and Anomaly Detection in Laser Powder Bed Fusion: Calibration, Data Mapping, and Feature Extraction
Laser powder bed fusion (LPBF) process can incur defects due to melt pool instabilities, spattering, temperature increase, and powder spread anomalies. Identifying defects through in-situ monitoring typically requires co…
3D geometryAnomaly DetectionDefect DetectionFabGPT: An Efficient Large Multimodal Model for Complex Wafer Defect Knowledge Queries
Intelligence is key to advancing integrated circuit (IC) fabrication. Recent breakthroughs in Large Multimodal Models (LMMs) have unlocked extraditionary abilities in understanding images and text, fostering intelligent …
Defect DetectionQuestion AnsweringA Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization
Anomaly synthesis strategies can effectively enhance unsupervised anomaly detection. However, existing strategies have limitations in the coverage and controllability of anomaly synthesis, particularly for weak defects t…
Anomaly DetectionDefect DetectionUnsupervised Anomaly DetectionExplainable Differential Privacy-Hyperdimensional Computing for Balancing Privacy and Transparency in Additive Manufacturing Monitoring
Machine Learning (ML) models integrated with in-situ sensing offer transformative solutions for defect detection in Additive Manufacturing (AM), but this integration brings critical challenges in safeguarding sensitive d…
Anomaly DetectionDefect DetectionLeveraging Latent Diffusion Models for Training-Free In-Distribution Data Augmentation for Surface Defect Detection
Defect detection is the task of identifying defects in production samples. Usually, defect detection classifiers are trained on ground-truth data formed by normal samples (negative data) and samples with defects (positiv…
Data AugmentationDefect DetectionImage GenerationUnified Anomaly Detection methods on Edge Device using Knowledge Distillation and Quantization
With the rapid advances in deep learning and smart manufacturing in Industry 4.0, there is an imperative for high-throughput, high-performance, and fully integrated visual inspection systems. Most anomaly detection appro…
Anomaly DetectionCPUDefect DetectionKnowledge Distillation+2Towards Reducing Data Acquisition and Labeling for Defect Detection using Simulated Data
In many manufacturing settings, annotating data for machine learning and computer vision is costly, but synthetic data can be generated at significantly lower cost. Substituting the real-world data with synthetic data is…
Defect DetectionDomain Adaptationobject-detectionObject DetectionLiteYOLO-ID: A Lightweight Object Detection Network for Insulator Defect Detection
Insulator defect detection is of great significance to ensure the normal operation of power transmission and distribution networks. In response to the problems of low speed, low accuracy, and difficulty in deploying to e…
Defect DetectionInsulator Defect DetectionModel Compressionobject-detection+1Faster Metallic Surface Defect Detection Using Deep Learning with Channel Shuffling
Deep learning has been constantly improving in recent years and a significant number of researchers have devoted themselves to the research of defect detection algorithms. Detection and recognition of small and complex t…
Defect DetectionA Comprehensive Survey on Machine Learning Driven Material Defect Detection
Material defects (MD) represent a primary challenge affecting product performance and giving rise to safety issues in related products. The rapid and accurate identification and localization of MD constitute crucial rese…
Defect DetectionSurveyGlobal-Regularized Neighborhood Regression for Efficient Zero-Shot Texture Anomaly Detection
Texture surface anomaly detection finds widespread applications in industrial settings. However, existing methods often necessitate gathering numerous samples for model training. Moreover, they predominantly operate with…
Anomaly DetectionDefect DetectionregressionA PRISMA Driven Systematic Review of Publicly Available Datasets for Benchmark and Model Developments for Industrial Defect Detection
Recent advancements in quality control across various industries have increasingly utilized the integration of video cameras and image processing for effective defect detection. A critical barrier to progress is the scar…
BenchmarkingDefect DetectionA Deep Learning-Augmented Stand-off Radar Scheme for Rapidly Detecting Tree Defects
Tree defect detection is crucial for the structural health screening of trees. Existing nondestructive testing (NDT) techniques for tree defect detection require time-consuming and labor-intensive measurement campaigns. …
Defect DetectionSAM-LAD: Segment Anything Model Meets Zero-Shot Logic Anomaly Detection
Visual anomaly detection is vital in real-world applications, such as industrial defect detection and medical diagnosis. However, most existing methods focus on local structural anomalies and fail to detect higher-level …
Anomaly DetectionDefect DetectionGraph AttentionMedical Diagnosis+1