Papers Defect Detection
“Defect Detection” 태그가 달린 논문 394편 · 필터 해제
Evaluating Text-to-Image Generative Models: An Empirical Study on Human Image Synthesis
In this paper, we present an empirical study introducing a nuanced evaluation framework for text-to-image (T2I) generative models, applied to human image synthesis. Our framework categorizes evaluations into two distinct…
Defect DetectionFairnessImage GenerationDefect Detection in Tire X-Ray Images: Conventional Methods Meet Deep Structures
This paper introduces a robust approach for automated defect detection in tire X-ray images by harnessing traditional feature extraction methods such as Local Binary Pattern (LBP) and Gray Level Co-Occurrence Matrix (GLC…
Defect DetectionFeature EngineeringA Large-scale Evaluation of Pretraining Paradigms for the Detection of Defects in Electroluminescence Solar Cell Images
Pretraining has been shown to improve performance in many domains, including semantic segmentation, especially in domains with limited labelled data. In this work, we perform a large-scale evaluation and benchmarking of …
BenchmarkingDefect DetectionSegmentationSemantic SegmentationPatchFlow: Leveraging a Flow-Based Model with Patch Features
Die casting plays a crucial role across various industries due to its ability to craft intricate shapes with high precision and smooth surfaces. However, surface defects remain a major issue that impedes die casting qu…
Anomaly DetectionDefect DetectionOn Trojan Signatures in Large Language Models of Code
Trojan signatures, as described by Fields et al. (2021), are noticeable differences in the distribution of the trojaned class parameters (weights) and the non-trojaned class parameters of the trojaned model, that can be …
Binary ClassificationDefect DetectionAdvancements in Point Cloud-Based 3D Defect Detection and Classification for Industrial Systems: A Comprehensive Survey
In recent years, 3D point clouds (PCs) have gained significant attention due to their diverse applications across various fields, such as computer vision (CV), condition monitoring (CM), virtual reality, robotics, autono…
Autonomous DrivingDefect DetectionMulti-class Road Defect Detection and Segmentation using Spatial and Channel-wise Attention for Autonomous Road Repairing
Road pavement detection and segmentation are critical for developing autonomous road repair systems. However, developing an instance segmentation method that simultaneously performs multi-class defect detection and segme…
Defect DetectionDiversityInstance SegmentationSegmentation+1Road Surface Defect Detection -- From Image-based to Non-image-based: A Survey
Ensuring traffic safety is crucial, which necessitates the detection and prevention of road surface defects. As a result, there has been a growing interest in the literature on the subject, leading to the development of …
Defect DetectionJoint Attention-Guided Feature Fusion Network for Saliency Detection of Surface Defects
Surface defect inspection plays an important role in the process of industrial manufacture and production. Though Convolutional Neural Network (CNN) based defect inspection methods have made huge leaps, they still confro…
Defect DetectionSaliency DetectionAn Insight into Security Code Review with LLMs: Capabilities, Obstacles, and Influential Factors
Security code review is a time-consuming and labor-intensive process typically requiring integration with automated security defect detection tools. However, existing security analysis tools struggle with poor generaliza…
Defect DetectionA 2D Sinogram-Based Approach to Defect Localization in Computed Tomography
The rise of deep learning has introduced a transformative era in the field of image processing, particularly in the context of computed tomography. Deep learning has made a significant contribution to the field of indust…
Deep LearningDefect DetectionImage ReconstructionPosition+1A Systematic Review of Available Datasets in Additive Manufacturing
In-situ monitoring incorporating data from visual and other sensor technologies, allows the collection of extensive datasets during the Additive Manufacturing (AM) process. These datasets have potential for determining t…
Defect DetectionXAI-Enhanced Semantic Segmentation Models for Visual Quality Inspection
Visual quality inspection systems, crucial in sectors like manufacturing and logistics, employ computer vision and machine learning for precise, rapid defect detection. However, their unexplained nature can hinder trust,…
Defect DetectionSegmentationSemantic SegmentationControllable Image Synthesis of Industrial Data Using Stable Diffusion
Training supervised deep neural networks that perform defect detection and segmentation requires large-scale fully-annotated datasets, which can be hard or even impossible to obtain in industrial environments. Generative…
Defect DetectionImage GenerationDistillation-based fabric anomaly detection
Unsupervised texture anomaly detection has been a concerning topic in a vast amount of industrial processes. Patterned textures inspection, particularly in the context of fabric defect detection, is indeed a widely encou…
Anomaly DetectionDefect DetectionDomain GeneralizationKnowledge Distillation+1YOLO algorithm with hybrid attention feature pyramid network for solder joint defect detection
Traditional manual detection for solder joint defect is no longer applied during industrial production due to low efficiency, inconsistent evaluation, high cost and lack of real-time data. A new approach has been propose…
Defect DetectionGenerative Model-Driven Synthetic Training Image Generation: An Approach to Cognition in Rail Defect Detection
Recent advancements in cognitive computing, with the integration of deep learning techniques, have facilitated the development of intelligent cognitive systems (ICS). This is particularly beneficial in the context of rai…
Data AugmentationDefect DetectionImage GenerationImage ReconstructionA Novel Approach for Defect Detection of Wind Turbine Blade Using Virtual Reality and Deep Learning
Wind turbines are subjected to continuous rotational stresses and unusual external forces such as storms, lightning, strikes by flying objects, etc., which may cause defects in turbine blades. Hence, it requires a period…
Defect DetectionUnityBoosting Defect Detection in Manufacturing using Tensor Convolutional Neural Networks
Defect detection is one of the most important yet challenging tasks in the quality control stage in the manufacturing sector. In this work, we introduce a Tensor Convolutional Neural Network (T-CNN) and examine its perfo…
Defect DetectionCRD: Collaborative Representation Distance for Practical Anomaly Detection
Visual defect detection plays an important role in intelligent industry. Patch based methods consider visual images as a collection of image patches according to positions, which have stronger discriminative ability for …
Anomaly DetectionComputational EfficiencyDefect DetectionGPU