Papers Defect Detection
“Defect Detection” 태그가 달린 논문 394편 · 필터 해제
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation
Pre-trained models for Natural Languages (NL) like BERT and GPT have been recently shown to transfer well to Programming Languages (PL) and largely benefit a broad set of code-related tasks. Despite their success, most c…
Clone DetectionCode GenerationCode SummarizationCode Translation+4Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set Framework
In this paper, we propose an efficient approach for industrial defect detection that is modeled based on anomaly detection using point pattern data. Most recent works use \textit{global features} for feature extraction t…
Anomaly DetectionDefect DetectionFew-Shot LearningTransfer LearningFast Accurate Defect Detection in Wafer Fabrication
A generic fast method for object classification is proposed. In addition, a method for dimensional reduction is presented. The presented algorithms have been applied to real-world data from chip fabrication successfully …
Defect DetectionS2D2Net: An Improved Approach For Robust Steel Surface Defects Diagnosis With Small Sample Learning
Surface defect recognition of products is a necessary process to guarantee the quality of industrial production. This paper proposes a hybrid model, S2D2Net (Steel Surface Defect Diagnosis Network), for an efficient and …
Defect DetectionDiversityRobust classificationSmall Data Image Classification+1Multi defect detection and analysis of electron microscopy images with deep learning
Electron microscopy is widely used to explore defects in crystal structures, but human detecting of defects is often time-consuming, error-prone, and unreliable, and is not scalable to large numbers of images or real-tim…
Deep LearningDefect DetectionA Deep Learning Based Automatic Defect Analysis Framework for In-situ TEM Ion Irradiations
Videos captured using Transmission Electron Microscopy (TEM) can encode details regarding the morphological and temporal evolution of a material by taking snapshots of the microstructure sequentially. However, manual ana…
Defect Detectionobject-detectionObject DetectionDRAEM -- A discriminatively trained reconstruction embedding for surface anomaly detection
Visual surface anomaly detection aims to detect local image regions that significantly deviate from normal appearance. Recent surface anomaly detection methods rely on generative models to accurately reconstruct the norm…
Anomaly ClassificationAnomaly DetectionAnomaly LocalizationAnomaly Segmentation+2TL-SDD: A Transfer Learning-Based Method for Surface Defect Detection with Few Samples
Surface defect detection plays an increasingly important role in manufacturing industry to guarantee the product quality. Many deep learning methods have been widely used in surface defect detection tasks, and have been …
Defect DetectionTransfer LearningA Cascaded Zoom-In Network for Patterned Fabric Defect Detection
Nowadays, Deep Convolutional Neural Networks (DCNNs) are widely used in fabric defect detection, which come with the cost of expensive training and complex model parameters. With the observation that most fabrics are def…
Defect DetectionReference-based Defect Detection Network
The defect detection task can be regarded as a realistic scenario of object detection in the computer vision field and it is widely used in the industrial field. Directly applying vanilla object detector to defect detect…
Defect Detectionobject-detectionObject DetectionRegion ProposalAn Uncertainty-Aware Deep Learning Framework for Defect Detection in Casting Products
Defects are unavoidable in casting production owing to the complexity of the casting process. While conventional human-visual inspection of casting products is slow and unproductive in mass productions, an automatic and …
Defect Detectionimage-classificationImage ClassificationTransfer Learning+1Optical Inspection of the Silicon Micro-strip Sensors for the CBM Experiment employing Artificial Intelligence
Optical inspection of 1191 silicon micro-strip sensors was performed using a custom made optical inspection setup, employing a machine-learning based approach for the defect analysis and subsequent quality assurance. Fur…
Defect DetectionOne-class Steel Detector Using Patch GAN Discriminator for Visualising Anomalous Feature Map
For steel product manufacturing in indoor factories, steel defect detection is important for quality control. For example, a steel sheet is extremely delicate, and must be accurately inspected. However, to maintain the p…
Anomaly DetectionDefect DetectionGenerative Adversarial Networkimage-classification+1Zero-sample surface defect detection and classification based on semantic feedback neural network
Defect detection and classification technology has changed from traditional artificial visual inspection to current intelligent automated inspection, but most of the current defect detection methods are training related …
AttributeDefect Detectionimage-classificationImage Classification+3Intelligent Vision Based Wear Forecasting on Surfaces of Machine Tool Elements
This paper addresses the ability to enable machines to automatically detect failures on machine tool components as well as estimating the severity of the failures, which is a critical step towards autonomous production m…
Defect DetectionPrognosisGenerative adversarial network with object detector discriminator for enhanced defect detection on ultrasonic B-scans
Non-destructive testing is a set of techniques for defect detection in materials. While the set of imaging techniques are manifold, ultrasonic imaging is the one used the most. The analysis is mainly performed by human i…
Data AugmentationDefect DetectionGenerative Adversarial Networkobject-detection+2Deep Unfolding of Iteratively Reweighted ADMM for Wireless RF Sensing
We address the detection of material defects, which are inside a layered material structure using compressive sensing based multiple-input and multiple-output (MIMO) wireless radar. Here, the strong clutter due to the re…
Compressive SensingDefect DetectionDrone-based AI and 3D Reconstruction for Digital Twin Augmentation
Digital Twin is an emerging technology at the forefront of Industry 4.0, with the ultimate goal of combining the physical space and the virtual space. To date, the Digital Twin concept has been applied in many engineerin…
3D ReconstructionDefect DetectionCoTexT: Multi-task Learning with Code-Text Transformer
We present CoTexT, a pre-trained, transformer-based encoder-decoder model that learns the representative context between natural language (NL) and programming language (PL). Using self-supervision, CoTexT is pre-trained …
Code GenerationCode SummarizationDecoderDefect Detection+2Deep Learning Based Steel Pipe Weld Defect Detection
Steel pipes are widely used in high-risk and high-pressure scenarios such as oil, chemical, natural gas, shale gas, etc. If there is some defect in steel pipes, it will lead to serious adverse consequences. Applying obje…
Deep LearningDefect DetectionObjectobject-detection+1