Papers Defect Detection
“Defect Detection” 태그가 달린 논문 394편 · 필터 해제
Semi-Supervised Defect Detection via Conditional Diffusion and CLIP-Guided Noise Filtering
In the realm of industrial quality inspection, defect detection stands as a critical component, particularly in high-precision, safety-critical sectors such as automotive components aerospace, and medical devices. Tradit…
Defect DetectionSupervised Defect DetectionYOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection
Surface defect detection in industrial scenarios is both crucial and technically demanding due to the wide variability in defect types, irregular shapes and sizes, fine-grained requirements, and complex material textures…
Defect DetectionHow Good Are Synthetic Requirements ? Evaluating LLM-Generated Datasets for AI4RE
The shortage of publicly available, labeled requirements datasets remains a major barrier to advancing Artificial Intelligence for Requirements Engineering (AI4RE). While Large Language Models offer promising capabilitie…
Defect DetectionDiversitySynthetic Data GenerationFrom Lab to Factory: Pitfalls and Guidelines for Self-/Unsupervised Defect Detection on Low-Quality Industrial Images
The detection and localization of quality-related problems in industrially mass-produced products has historically relied on manual inspection, which is costly and error-prone. Machine learning has the potential to repla…
Defect DetectionPlug-and-Play with 2.5D Artifact Reduction Prior for Fast and Accurate Industrial Computed Tomography Reconstruction
Cone-beam X-ray computed tomography (XCT) is an essential imaging technique for generating 3D reconstructions of internal structures, with applications ranging from medical to industrial imaging. Producing high-quality r…
3D ReconstructionDefect DetectionESRPCB: an Edge guided Super-Resolution model and Ensemble learning for tiny Printed Circuit Board Defect detection
Printed Circuit Boards (PCBs) are critical components in modern electronics, which require stringent quality control to ensure proper functionality. However, the detection of defects in small-scale PCBs images poses sign…
Defect DetectionEnsemble LearningSuper-ResolutionJ-DDL: Surface Damage Detection and Localization System for Fighter Aircraft
Ensuring the safety and extended operational life of fighter aircraft necessitates frequent and exhaustive inspections. While surface defect detection is feasible for human inspectors, manual methods face critical limita…
Defect DetectionDeep Learning-based Multi Project InP Wafer Simulation for Unsupervised Surface Defect Detection
Quality management in semiconductor manufacturing often relies on template matching with known golden standards. For Indium-Phosphide (InP) multi-project wafer manufacturing, low production scale and high design variabil…
Defect DetectionManagementTemplate MatchingUsing In-Context Learning for Automatic Defect Labelling of Display Manufacturing Data
This paper presents an AI-assisted auto-labeling system for display panel defect detection that leverages in-context learning capabilities. We adopt and enhance the SegGPT architecture with several domain-specific traini…
Defect DetectionIn-Context LearningThe Impact of Software Testing with Quantum Optimization Meets Machine Learning
Modern software systems complexity challenges efficient testing, as traditional machine learning (ML) struggles with large test suites. This research presents a hybrid framework integrating Quantum Annealing with ML to o…
Defect Detectionsoftware testingTowards Practical Defect-Focused Automated Code Review
The complexity of code reviews has driven efforts to automate review comments, but prior approaches oversimplify this task by treating it as snippet-level code-to-text generation and relying on text similarity metrics li…
Defect DetectionText Generationtext similarityImplicit Neural Shape Optimization for 3D High-Contrast Electrical Impedance Tomography
We present a novel implicit neural shape optimization framework for 3D high-contrast Electrical Impedance Tomography (EIT), addressing scenarios where conductivity exhibits sharp discontinuities across material interface…
Defect DetectionAdvancing Software Quality: A Standards-Focused Review of LLM-Based Assurance Techniques
Software Quality Assurance (SQA) is critical for delivering reliable, secure, and efficient software products. The Software Quality Assurance Process aims to provide assurance that work products and processes comply with…
Defect DetectionDefect Detection in Photolithographic Patterns Using Deep Learning Models Trained on Synthetic Data
In the photolithographic process vital to semiconductor manufacturing, various types of defects appear during EUV pattering. Due to ever-shrinking pattern size, these defects are extremely small and cause false or missed…
Defect Detectionobject-detectionObject DetectionDifferentiable NMS via Sinkhorn Matching for End-to-End Fabric Defect Detection
Fabric defect detection confronts two fundamental challenges. First, conventional non-maximum suppression disrupts gradient flow, which hinders genuine end-to-end learning. Second, acquiring pixel-level annotations at in…
Defect Detectionobject-detectionObject DetectionPhotovoltaic Defect Image Generator with Boundary Alignment Smoothing Constraint for Domain Shift Mitigation
Accurate defect detection of photovoltaic (PV) cells is critical for ensuring quality and efficiency in intelligent PV manufacturing systems. However, the scarcity of rich defect data poses substantial challenges for eff…
Defect DetectionDiversityCXR-AD: Component X-ray Image Dataset for Industrial Anomaly Detection
Internal defect detection constitutes a critical process in ensuring component quality, for which anomaly detection serves as an effective solution. However, existing anomaly detection datasets predominantly focus on sur…
Anomaly DetectionDefect DetectionZero-Shot LearningEnhancing Glass Defect Detection with Diffusion Models: Addressing Imbalanced Datasets in Manufacturing Quality Control
Visual defect detection in industrial glass manufacturing remains a critical challenge due to the low frequency of defective products, leading to imbalanced datasets that limit the performance of deep learning models and…
Data AugmentationDefect DetectionDenoisingimage-classification+2Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing
The deployment of machine learning (ML)-based process monitoring systems has significantly advanced additive manufacturing (AM) by enabling real-time defect detection, quality assessment, and process optimization. Howeve…
Defect DetectionTransfer LearningSteelBlastQC: Shot-blasted Steel Surface Dataset with Interpretable Detection of Surface Defects
Automating the quality control of shot-blasted steel surfaces is crucial for improving manufacturing efficiency and consistency. This study presents a dataset of 1654 labeled RGB images (512x512) of steel surfaces, class…
Defect Detection