Papers Defect Detection
“Defect Detection” 태그가 달린 논문 394편 · 필터 해제
Defect Transformer: An Efficient Hybrid Transformer Architecture for Surface Defect Detection
Surface defect detection is an extremely crucial step to ensure the quality of industrial products. Nowadays, convolutional neural networks (CNNs) based on encoder-decoder architecture have achieved tremendous success in…
Computational EfficiencyDecoderDefect DetectionPositionFacilitated machine learning for image-based fruit quality assessment
Image-based machine learning models can be used to make the sorting and grading of agricultural products more efficient. In many regions, implementing such systems can be difficult due to the lack of centralization and a…
BIG-bench Machine LearningClassificationDefect DetectionImage ClassificationFew-shot incremental learning in the context of solar cell quality inspection
In industry, Deep Neural Networks have shown high defect detection rates surpassing other more traditional manual feature engineering based proposals. This has been achieved mainly through supervised training where a gre…
Defect DetectionFeature EngineeringIncremental LearningProductive Reproducible Workflows for DNNs: A Case Study for Industrial Defect Detection
As Deep Neural Networks (DNNs) have become an increasingly ubiquitous workload, the range of libraries and tooling available to aid in their development and deployment has grown significantly. Scalable, production qualit…
CPUDefect DetectionGPURaspberry Pi 4A Survey of Detection Methods for Die Attachment and Wire Bonding Defects in Integrated Circuit Manufacturing
Defect detection plays a vital role in the manufacturing process of integrated circuits (ICs). Die attachment and wire bonding are two steps of the manufacturing process that determine the power and signal transmission q…
Defect DetectionSurveyDeep Gradient Learning for Efficient Camouflaged Object Detection
This paper introduces DGNet, a novel deep framework that exploits object gradient supervision for camouflaged object detection (COD). It decouples the task into two connected branches, i.e., a context and a texture encod…
Defect DetectionObjectobject-detectionObject Detection+2A Coupling Enhancement Algorithm for ZrO2 Ceramic Bearing Ball Surface Defect Detection Based on Cartoon-texture Decomposition Model and Multi-Scale Filtering Method
This study aimed to improve the surface defect detection accuracy of ZrO2 ceramic bearing balls. Combined with the noise damage of the image samples, a surface defect detection method for ZrO2 ceramic bearing balls based…
Defect DetectionDenoisingImage DenoisingSSIMSelf-Supervised Masking for Unsupervised Anomaly Detection and Localization
Recently, anomaly detection and localization in multimedia data have received significant attention among the machine learning community. In real-world applications such as medical diagnosis and industrial defect detecti…
Anomaly DetectionAnomaly LocalizationDefect DetectionMedical Diagnosis+2Sibylvariant Transformations for Robust Text Classification
The vast majority of text transformation techniques in NLP are inherently limited in their ability to expand input space coverage due to an implicit constraint to preserve the original class label. In this work, we propo…
Adversarial RobustnessDefect DetectionGeneral ClassificationText ClassificationCODE-MVP: Learning to Represent Source Code from Multiple Views with Contrastive Pre-Training
Recent years have witnessed increasing interest in code representation learning, which aims to represent the semantics of source code into distributed vectors. Currently, various works have been proposed to represent the…
Contrastive LearningDefect DetectionRepresentation LearningRetrievalMemSeg: A semi-supervised method for image surface defect detection using differences and commonalities
Under the semi-supervised framework, we propose an end-to-end memory-based segmentation network (MemSeg) to detect surface defects on industrial products. Considering the small intra-class variance of products in the sam…
Anomaly DetectionDefect DetectionRobust classificationCellDefectNet: A Machine-designed Attention Condenser Network for Electroluminescence-based Photovoltaic Cell Defect Inspection
Photovoltaic cells are electronic devices that convert light energy to electricity, forming the backbone of solar energy harvesting systems. An essential step in the manufacturing process for photovoltaic cells is visual…
Defect DetectionLightDefectNet: A Highly Compact Deep Anti-Aliased Attention Condenser Neural Network Architecture for Light Guide Plate Surface Defect Detection
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. An essential step in the manufacturing of light guide pla…
Defect DetectionA Survey on Unsupervised Anomaly Detection Algorithms for Industrial Images
In line with the development of Industry 4.0, surface defect detection/anomaly detection becomes a topical subject in the industry field. Improving efficiency as well as saving labor costs has steadily become a matter of…
Anomaly DetectionDefect DetectionUnsupervised Anomaly DetectionOne-Class Model for Fabric Defect Detection
An automated and accurate fabric defect inspection system is in high demand as a replacement for slow, inconsistent, error-prone, and expensive human operators in the textile industry. Previous efforts focused on certain…
Defect DetectionmodelAddressing Leakage in Self-Supervised Contextualized Code Retrieval
We address contextualized code retrieval, the search for code snippets helpful to fill gaps in a partial input program. Our approach facilitates a large-scale self-supervised contrastive training by splitting source code…
Defect DetectionRetrievalNPC: Neuron Path Coverage via Characterizing Decision Logic of Deep Neural Networks
Deep learning has recently been widely applied to many applications across different domains, e.g., image classification and audio recognition. However, the quality of Deep Neural Networks (DNNs) still raises concerns in…
Defect DetectionDNN Testingimage-classificationImage Classification+1An Interactive Explanatory AI System for Industrial Quality Control
Machine learning based image classification algorithms, such as deep neural network approaches, will be increasingly employed in critical settings such as quality control in industry, where transparency and comprehensibi…
BIG-bench Machine LearningDefect Detectionimage-classificationImage Classification+1Surface Defect Detection and Evaluation for Marine Vessels using Multi-Stage Deep Learning
Detecting and evaluating surface coating defects is important for marine vessel maintenance. Currently, the assessment is carried out manually by qualified inspectors using international standards and their own experienc…
Defect DetectionSegmentationA Continual Learning Framework for Adaptive Defect Classification and Inspection
Machine-vision-based defect classification techniques have been widely adopted for automatic quality inspection in manufacturing processes. This article describes a general framework for classifying defects from high vol…
ClassificationContinual LearningDefect Detectionimage-classification+1