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Defect Detection

Papers

Showing 2650 of 394 papers

TitleStatusHype
DSR -- A dual subspace re-projection network for surface anomaly detectionCode1
Deep Gradient Learning for Efficient Camouflaged Object DetectionCode1
One-Class Model for Fabric Defect DetectionCode1
LF-YOLO: A Lighter and Faster YOLO for Weld Defect Detection of X-ray ImageCode1
Fully Convolutional Cross-Scale-Flows for Image-based Defect DetectionCode1
ChangeChip: A Reference-Based Unsupervised Change Detection for PCB Defect DetectionCode1
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and GenerationCode1
Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set FrameworkCode1
DRAEM -- A discriminatively trained reconstruction embedding for surface anomaly detectionCode1
CoTexT: Multi-task Learning with Code-Text TransformerCode1
Deep Learning Based Steel Pipe Weld Defect DetectionCode1
A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly DetectionCode1
Mixed supervision for surface-defect detection: from weakly to fully supervised learningCode1
CutPaste: Self-Supervised Learning for Anomaly Detection and LocalizationCode1
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and GenerationCode1
DRAEM - A Discriminatively Trained Reconstruction Embedding for Surface Anomaly DetectionCode1
Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing FlowsCode1
End-to-end training of a two-stage neural network for defect detectionCode1
Unsupervised Pixel-level Road Defect Detection via Adversarial Image-to-Frequency TransformCode1
Semi-supervised Anomaly Detection using AutoEncodersCode1
Segmentation-Based Deep-Learning Approach for Surface-Defect DetectionCode1
Online PCB Defect Detector On A New PCB Defect DatasetCode1
Semi-Supervised Defect Detection via Conditional Diffusion and CLIP-Guided Noise FilteringCode0
How Good Are Synthetic Requirements ? Evaluating LLM-Generated Datasets for AI4RECode0
YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection0
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