Papers Defect Detection
“Defect Detection” 태그가 달린 논문 394편 · 필터 해제
Review of Machine Learning Methods for Additive Manufacturing of Functionally Graded Materials
Additive Manufacturing (AM) is a transformative manufacturing technology enabling direct fabrication of complex parts layer-be-layer from 3D modeling data. Among AM applications, the fabrication of Functionally Graded Ma…
Defect DetectionPhotonic Accelerators for Image Segmentation in Autonomous Driving and Defect Detection
Photonic computing promises faster and more energy-efficient deep neural network (DNN) inference than traditional digital hardware. Advances in photonic computing can have profound impacts on applications such as autonom…
Autonomous DrivingDefect DetectionImage SegmentationSegmentation+1Application of reciprocity for facilitation of wave field visualization and defect detection
The motion visualization in a structural component was studied for defect detection. Elastic motions were excited by hammer impacts at multiple points and received by an accelerometer at a fixed point. Reciprocity in ela…
Defect DetectionPositionvalidGlobal Context Aggregation Network for Lightweight Saliency Detection of Surface Defects
Surface defect inspection is a very challenging task in which surface defects usually show weak appearances or exist under complex backgrounds. Most high-accuracy defect detection methods require expensive computation an…
DecoderDefect DetectionGPUSaliency DetectionCINFormer: Transformer network with multi-stage CNN feature injection for surface defect segmentation
Surface defect inspection is of great importance for industrial manufacture and production. Though defect inspection methods based on deep learning have made significant progress, there are still some challenges for thes…
Defect DetectionFAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly Detection
Image reconstruction-based anomaly detection models are widely explored in industrial visual inspection. However, existing models usually suffer from the trade-off between normal reconstruction fidelity and abnormal reco…
Anomaly DetectionDefect DetectionImage ReconstructionImage RestorationAutoencoder-Based Visual Anomaly Localization for Manufacturing Quality Control
Manufacturing industries require efficient and voluminous production of high-quality finished goods. In the context of Industry 4.0, visual anomaly detection poses an optimistic solution for automatically controlled prod…
Anomaly DetectionAnomaly LocalizationDefect DetectionManufacturing Quality ControlImproving Deep Learning-based Defect Detection on Window Frames with Image Processing Strategies
Detecting subtle defects in window frames, including dents and scratches, is vital for upholding product integrity and sustaining a positive brand perception. Conventional machine vision systems often struggle to identif…
Defect DetectionImage AugmentationImage EnhancementA study on the impact of pre-trained model on Just-In-Time defect prediction
Previous researchers conducting Just-In-Time (JIT) defect prediction tasks have primarily focused on the performance of individual pre-trained models, without exploring the relationship between different pre-trained mode…
Defect DetectionDefect Detection in Synthetic Fibre Ropes using Detectron2 Framework
Fibre ropes with the latest technology have emerged as an appealing alternative to steel ropes for offshore industries due to their lightweight and high tensile strength. At the same time, frequent inspection of these ro…
Defect DetectionInstance SegmentationSemantic SegmentationGap and Overlap Detection in Automated Fiber Placement
The identification and correction of manufacturing defects, particularly gaps and overlaps, are crucial for ensuring high-quality composite parts produced through Automated Fiber Placement (AFP). These imperfections are …
Defect DetectionEvaluating Deep Learning Assisted Automated Aquaculture Net Pens Inspection Using ROV
In marine aquaculture, inspecting sea cages is an essential activity for managing both the facilities' environmental impact and the quality of the fish development process. Fish escape from fish farms into the open sea d…
Deep LearningDefect DetectionAutonomous Underwater Robotic System for Aquaculture Applications
Aquaculture is a thriving food-producing sector producing over half of the global fish consumption. However, these aquafarms pose significant challenges such as biofouling, vegetation, and holes within their net pens and…
Defect DetectionREB: Reducing Biases in Representation for Industrial Anomaly Detection
Existing representation-based methods usually conduct industrial anomaly detection in two stages: obtain feature representations with a pre-trained model and perform distance measures for anomaly detection. Among them, K…
Anomaly DetectionDefect DetectionDomain AdaptationRetrieval+1Multi-Scale Memory Comparison for Zero-/Few-Shot Anomaly Detection
Anomaly detection has gained considerable attention due to its broad range of applications, particularly in industrial defect detection. To address the challenges of data collection, researchers have introduced zero-/few…
Anomaly DetectionDefect DetectionNovelty DetectionHigh-Performance Fine Defect Detection in Artificial Leather Using Dual Feature Pool Object Detection
In this study, the structural problems of the YOLOv5 model were analyzed emphatically. Based on the characteristics of fine defects in artificial leather, four innovative structures, namely DFP, IFF, AMP, and EOS, were d…
Defect Detectionobject-detectionObject DetectionLaFiCMIL: Rethinking Large File Classification from the Perspective of Correlated Multiple Instance Learning
Transfomer-based models have significantly advanced natural language processing, in particular the performance in text classification tasks. Nevertheless, these models face challenges in processing large files, primarily…
Android Malware DetectionClassificationDefect DetectionDocument Classification+7YOLOv8 for Defect Inspection of Hexagonal Directed Self-Assembly Patterns: A Data-Centric Approach
Shrinking pattern dimensions leads to an increased variety of defect types in semiconductor devices. This has spurred innovation in patterning approaches such as Directed self-assembly (DSA) for which no traditional, aut…
Defect DetectionForestMonkey: Toolkit for Reasoning with AI-based Defect Detection and Classification Models
Artificial intelligence (AI) reasoning and explainable AI (XAI) tasks have gained popularity recently, enabling users to explain the predictions or decision processes of AI models. This paper introduces Forest Monkey (FM…
Defect DetectionExplainable Artificial Intelligence (XAI)A real-time material breakage detection for offshore wind turbines based on improved neural network algorithm
The integrity of offshore wind turbines, pivotal for sustainable energy generation, is often compromised by surface material defects. Despite the availability of various detection techniques, limitations persist regardin…
Defect Detectionobject-detectionObject Detection