Papers Defect Detection
“Defect Detection” 태그가 달린 논문 394편 · 필터 해제
In-situ Anomaly Detection in Additive Manufacturing with Graph Neural Networks
Transforming a design into a high-quality product is a challenge in metal additive manufacturing due to rare events which can cause defects to form. Detecting these events in-situ could, however, reduce inspection costs,…
Anomaly DetectionDefect DetectionHuman-machine knowledge hybrid augmentation method for surface defect detection based few-data learning
Visual-based defect detection is a crucial but challenging task in industrial quality control. Most mainstream methods rely on large amounts of existing or related domain data as auxiliary information. However, in actual…
Defect DetectionISSTAD: Incremental Self-Supervised Learning Based on Transformer for Anomaly Detection and Localization
In the realm of machine learning, the study of anomaly detection and localization within image data has gained substantial traction, particularly for practical applications such as industrial defect detection. While the …
Anomaly DetectionAnomaly LocalizationData AugmentationDefect Detection+2ARMBench: An Object-centric Benchmark Dataset for Robotic Manipulation
This paper introduces Amazon Robotic Manipulation Benchmark (ARMBench), a large-scale, object-centric benchmark dataset for robotic manipulation in the context of a warehouse. Automation of operations in modern warehouse…
Defect DetectionInstance SegmentationObjectSemantic SegmentationMachine-learned Adversarial Attacks against Fault Prediction Systems in Smart Electrical Grids
In smart electrical grids, fault detection tasks may have a high impact on society due to their economic and critical implications. In the recent years, numerous smart grid applications, such as defect detection and load…
Defect DetectionFault DetectionFault localizationLoad ForecastingDefect detection using weakly supervised learning
In many real-world scenarios, obtaining large amounts of labeled data can be a daunting task. Weakly supervised learning techniques have gained significant attention in recent years as an alternative to traditional super…
Defect DetectionWeakly-supervised LearningDefect Detection Approaches Based on Simulated Reference Image
This work is addressing the problem of defect anomaly detection based on a clean reference image. Specifically, we focus on SEM semiconductor defects in addition to several natural image anomalies. There are well-known m…
Anomaly DetectionDefect DetectionSSGD: A smartphone screen glass dataset for defect detection
Interactive devices with touch screen have become commonly used in various aspects of daily life, which raises the demand for high production quality of touch screen glass. While it is desirable to develop effective defe…
Defect Detectionobject-detectionObject DetectionDiversity-Measurable Anomaly Detection
Reconstruction-based anomaly detection models achieve their purpose by suppressing the generalization ability for anomaly. However, diverse normal patterns are consequently not well reconstructed as well. Although some e…
Anomaly DetectionAnomaly Detection In Surveillance VideosDefect DetectionDiversity+1Photovoltaic Panel Defect Detection Based on Ghost Convolution with BottleneckCSP and Tiny Target Prediction Head Incorporating YOLOv5
Photovoltaic (PV) panel surface-defect detection technology is crucial for the PV industry to perform smart maintenance. Using computer vision technology to detect PV panel surface defects can ensure better accuracy whil…
Defect DetectionTransferD2: Automated Defect Detection Approach in Smart Manufacturing using Transfer Learning Techniques
Quality assurance is crucial in the smart manufacturing industry as it identifies the presence of defects in finished products before they are shipped out. Modern machine learning techniques can be leveraged to provide r…
Defect DetectionTransfer LearningOptimizing YOLOv7 for Semiconductor Defect Detection
The field of object detection using Deep Learning (DL) is constantly evolving with many new techniques and models being proposed. YOLOv7 is a state-of-the-art object detector based on the YOLO family of models which have…
Defect DetectionObjectobject-detectionObject DetectionA lightweight network for photovoltaic cell defect detection in electroluminescence images based on neural architecture search and knowledge distillation
Nowadays, the rapid development of photovoltaic(PV) power stations requires increasingly reliable maintenance and fault diagnosis of PV modules in the field. Due to the effectiveness, convolutional neural network (CNN) h…
Data AugmentationDefect DetectionFault DiagnosisKnowledge Distillation+1IH-ViT: Vision Transformer-based Integrated Circuit Appear-ance Defect Detection
For the problems of low recognition rate and slow recognition speed of traditional detection methods in IC appearance defect detection, we propose an IC appearance defect detection algo-rithm IH-ViT. Our proposed model t…
Decision MakingDefect DetectionImage SegmentationSemantic SegmentationLearning Trustworthy Model from Noisy Labels based on Rough Set for Surface Defect Detection
In the surface defect detection, there are some suspicious regions that cannot be uniquely classified as abnormal or normal. The annotating of suspicious regions is easily affected by factors such as workers' emotional f…
Defect DetectionA Lightweight Reconstruction Network for Surface Defect Inspection
Currently, most deep learning methods cannot solve the problem of scarcity of industrial product defect samples and significant differences in characteristics. This paper proposes an unsupervised defect detection algorit…
Defect DetectionImage ReconstructionHigh-Throughput, High-Performance Deep Learning-Driven Light Guide Plate Surface Visual Quality Inspection Tailored for Real-World Manufacturing Environments
Light guide plates are essential optical components widely used in a diverse range of applications ranging from medical lighting fixtures to back-lit TV displays. In this work, we introduce a fully-integrated, high-throu…
Defect DetectionEdge-computingVocal Bursts Intensity PredictionSynthetic Data Augmentation Using GAN For Improved Automated Visual Inspection
Quality control is a crucial activity performed by manufacturing companies to ensure their products conform to the requirements and specifications. The introduction of artificial intelligence models enables to automate t…
Data AugmentationDefect DetectionRobust Anomaly Map Assisted Multiple Defect Detection with Supervised Classification Techniques
Industry 4.0 aims to optimize the manufacturing environment by leveraging new technological advances, such as new sensing capabilities and artificial intelligence. The DRAEM technique has shown state-of-the-art performan…
ClassificationDefect DetectionSemi-Siamese Network for Robust Change Detection Across Different Domains with Applications to 3D Printing
Automatic defect detection for 3D printing processes, which shares many characteristics with change detection problems, is a vital step for quality control of 3D printed products. However, there are some critical challen…
Change DetectionDefect DetectionImage SegmentationSemantic Segmentation