Papers Defect Detection
“Defect Detection” 태그가 달린 논문 394편 · 필터 해제
Diffusion-based Image Generation for In-distribution Data Augmentation in Surface Defect Detection
In this study, we show that diffusion models can be used in industrial scenarios to improve the data augmentation procedure in the context of surface defect detection. In general, defect detection classifiers are trained…
Data AugmentationDefect DetectionImage GenerationA Study on Unsupervised Anomaly Detection and Defect Localization using Generative Model in Ultrasonic Non-Destructive Testing
In recent years, the deterioration of artificial materials used in structures has become a serious social issue, increasing the importance of inspections. Non-destructive testing is gaining increased demand due to its ca…
Anomaly DetectionDefect Detectionobject-detectionObject Detection+1MINet: Multi-scale Interactive Network for Real-time Salient Object Detection of Strip Steel Surface Defects
The automated surface defect detection is a fundamental task in industrial production, and the existing saliencybased works overcome the challenging scenes and give promising detection results. However, the cutting-edge …
CPUDefect DetectionGPUobject-detection+2Aerial Inspection of High-Voltage Power Lines Using YOLOv8 Real-Time Object Detector
The aerial inspection of electricity infrastructure is gaining high interest due to the rapid advancements in unmanned aerial vehicle (UAV) technology, which has proven to be a cost- and time-effective solution for deplo…
CPUDefect DetectionLine DetectionIncomplete Multimodal Industrial Anomaly Detection via Cross-Modal Distillation
Recent studies of multimodal industrial anomaly detection (IAD) based on 3D point clouds and RGB images have highlighted the importance of exploiting the redundancy and complementarity among modalities for accurate class…
Anomaly DetectionDefect DetectionMemoryMamba: Memory-Augmented State Space Model for Defect Recognition
As automation advances in manufacturing, the demand for precise and sophisticated defect detection technologies grows. Existing vision models for defect recognition methods are insufficient for handling the complexities …
Defect DetectionDefect Localization Using Region of Interest and Histogram-Based Enhancement Approaches in 3D-Printing
Additive manufacturing (AM), particularly 3D printing, has revolutionized the production of complex structures across various industries. However, ensuring quality and detecting defects in 3D-printed objects remain signi…
Computational EfficiencyDecision MakingDefect DetectionMachine Learning for Pre/Post Flight UAV Rotor Defect Detection Using Vibration Analysis
Unmanned Aerial Vehicles (UAVs) will be critical infrastructural components of future smart cities. In order to operate efficiently, UAV reliability must be ensured by constant monitoring for faults and failures. To this…
Defect DetectionDimensionality ReductionPV-S3: Advancing Automatic Photovoltaic Defect Detection using Semi-Supervised Semantic Segmentation of Electroluminescence Images
Photovoltaic (PV) systems allow us to tap into all abundant solar energy, however they require regular maintenance for high efficiency and to prevent degradation. Traditional manual health check, using Electroluminescenc…
Defect DetectionSegmentationSemantic SegmentationSemi-Supervised Semantic SegmentationIn-situ process monitoring and adaptive quality enhancement in laser additive manufacturing: a critical review
Laser Additive Manufacturing (LAM) presents unparalleled opportunities for fabricating complex, high-performance structures and components with unique material properties. Despite these advancements, achieving consistent…
BenchmarkingDecision MakingDefect DetectionFault Diagnosis+1CarcassFormer: An End-to-end Transformer-based Framework for Simultaneous Localization, Segmentation and Classification of Poultry Carcass Defect
In the food industry, assessing the quality of poultry carcasses during processing is a crucial step. This study proposes an effective approach for automating the assessment of carcass quality without requiring skilled l…
Defect DetectionAssessing The Impact of CNN Auto Encoder-Based Image Denoising on Image Classification Tasks
Images captured from the real world are often affected by different types of noise, which can significantly impact the performance of Computer Vision systems and the quality of visual data. This study presents a novel ap…
Binary ClassificationClassificationDefect DetectionDenoising+4AI-Guided Defect Detection Techniques to Model Single Crystal Diamond Growth
From a process development perspective, diamond growth via chemical vapor deposition has made significant strides. However, challenges persist in achieving high quality and large-area material production. These difficult…
Active LearningDefect DetectionSemantic SegmentationAutomatic Defect Detection in Sewer Network Using Deep Learning Based Object Detector
Maintaining sewer systems in large cities is important, but also time and effort consuming, because visual inspections are currently done manually. To reduce the amount of aforementioned manual work, defects within sewer…
Defect DetectionObjectobject-detectionObject DetectionTowards Improved Semiconductor Defect Inspection for high-NA EUVL based on SEMI-SuperYOLO-NAS
Due to potential pitch reduction, the semiconductor industry is adopting High-NA EUVL technology. However, its low depth of focus presents challenges for High Volume Manufacturing. To address this, suppliers are explorin…
Data AugmentationDefect DetectionStochastic Geometry Models for Texture Synthesis of Machined Metallic Surfaces: Sandblasting and Milling
Training defect detection algorithms for visual surface inspection systems requires a large and representative set of training data. Often there is not enough real data available which additionally cannot cover the varie…
Defect DetectionTexture SynthesisOCR is All you need: Importing Multi-Modality into Image-based Defect Detection System
Automatic optical inspection (AOI) plays a pivotal role in the manufacturing process, predominantly leveraging high-resolution imaging instruments for scanning purposes. It detects anomalies by analyzing image textures o…
AllDecision MakingDefect DetectionOptical Character Recognition+1LERENet: Eliminating Intra-class Differences for Metal Surface Defect Few-shot Semantic Segmentation
Few-shot segmentation models excel in metal defect detection due to their rapid generalization ability to new classes and pixel-level segmentation, rendering them ideal for addressing data scarcity issues and achieving r…
Defect DetectionFew-Shot Semantic SegmentationSemantic SegmentationOpen Stamped Parts Dataset
We present the Open Stamped Parts Dataset (OSPD), featuring synthetic and real images of stamped metal sheets for auto manufacturing. The real part images, captured from 7 cameras, consist of 7,980 unlabeled images and 1…
Defect DetectionAchieving Pareto Optimality using Efficient Parameter Reduction for DNNs in Resource-Constrained Edge Environment
This paper proposes an optimization of an existing Deep Neural Network (DNN) that improves its hardware utilization and facilitates on-device training for resource-constrained edge environments. We implement efficient pa…
Defect Detectionimage-classificationImage ClassificationTransfer Learning