{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/defect-detection/papers/2","list_of":"/task/defect-detection","task":"Defect Detection","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":2,"pages_in_order":4,"rows_per_page":100,"rows":[101,200],"of":394,"counts":{"archive_papers_tagged":394,"with_a_code_link":86,"where_syntology_ran_a_sample":14,"not_listed_spam_title":0,"listed":394,"listed_where_code_ran":14,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":12,"every_run_a_failure_of_syntologys_instrument":2,"listed_with_a_run_with_no_instrument_failure":12,"listed_every_run_a_failure_of_syntologys_instrument":2,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/defect-detection","prev":"/task/defect-detection","next":"/task/defect-detection/papers/3","papers":[{"url":null,"slug":"cxr-ad-component-x-ray-image-dataset-for","title":"CXR-AD: Component X-ray Image Dataset for Industrial Anomaly Detection","date":"2025-05-06","arxiv_id":"2505.03412","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-glass-defect-detection-with","title":"Enhancing Glass Defect Detection with Diffusion Models: Addressing Imbalanced Datasets in Manufacturing Quality Control","date":"2025-05-06","arxiv_id":"2505.03134","repositories_listed":0,"syntology":null},{"url":null,"slug":"redundancy-analysis-and-mitigation-for","title":"Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing","date":"2025-04-30","arxiv_id":"2504.21317","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-signal-matrix-based-local-flaw-detection","title":"A Signal Matrix-Based Local Flaw Detection Framework for Steel Wire Ropes Using Convolutional Neural Networks","date":"2025-04-15","arxiv_id":"2504.10952","repositories_listed":0,"syntology":null},{"url":null,"slug":"cfis-yolo-a-lightweight-multi-scale-fusion","title":"CFIS-YOLO: A Lightweight Multi-Scale Fusion Network for Edge-Deployable Wood Defect Detection","date":"2025-04-15","arxiv_id":"2504.11305","repositories_listed":0,"syntology":null},{"url":null,"slug":"event-based-civil-infrastructure-visual","title":"Event-based Civil Infrastructure Visual Defect Detection: ev-CIVIL Dataset and Benchmark","date":"2025-04-08","arxiv_id":"2504.05679","repositories_listed":0,"syntology":null},{"url":null,"slug":"semiconductor-wafer-map-defect-classification","title":"Semiconductor Wafer Map Defect Classification with Tiny Vision Transformers","date":"2025-04-03","arxiv_id":"2504.02494","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-preserving-transformations-as","title":"Semantic-Preserving Transformations as Mutation Operators: A Study on Their Effectiveness in Defect Detection","date":"2025-03-30","arxiv_id":"2503.23448","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-surface-defect-detection-from","title":"Multimodal surface defect detection from wooden logs for sawing optimization","date":"2025-03-27","arxiv_id":"2503.21367","repositories_listed":0,"syntology":null},{"url":null,"slug":"small-object-detection-a-comprehensive-survey","title":"Small Object Detection: A Comprehensive Survey on Challenges, Techniques and Real-World Applications","date":"2025-03-26","arxiv_id":"2503.20516","repositories_listed":0,"syntology":null},{"url":null,"slug":"eiad-explainable-industrial-anomaly-detection","title":"EIAD: Explainable Industrial Anomaly Detection Via Multi-Modal Large Language Models","date":"2025-03-18","arxiv_id":"2503.14162","repositories_listed":0,"syntology":null},{"url":null,"slug":"fully-synthetic-training-for-visual-quality","title":"Fully-Synthetic Training for Visual Quality Inspection in Automotive Production","date":"2025-03-12","arxiv_id":"2503.09354","repositories_listed":0,"syntology":null},{"url":"/paper/isp-ad-a-large-scale-real-world-dataset-for","slug":"isp-ad-a-large-scale-real-world-dataset-for","title":"ISP-AD: A Large-Scale Real-World Dataset for Advancing Industrial Anomaly Detection with Synthetic and Real Defects","date":"2025-03-06","arxiv_id":"2503.04997","repositories_listed":0,"syntology":null},{"url":null,"slug":"ai-driven-multi-stage-computer-vision-system","title":"AI-Driven Multi-Stage Computer Vision System for Defect Detection in Laser-Engraved Industrial Nameplates","date":"2025-03-05","arxiv_id":"2503.03395","repositories_listed":0,"syntology":null},{"url":null,"slug":"pa-clip-enhancing-zero-shot-anomaly-detection","title":"PA-CLIP: Enhancing Zero-Shot Anomaly Detection through Pseudo-Anomaly Awareness","date":"2025-03-03","arxiv_id":"2503.01292","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-adaptive-gamma-context-aware-ssm-based","title":"Self-Adaptive Gamma Context-Aware SSM-based Model for Metal Defect Detection","date":"2025-03-03","arxiv_id":"2503.01234","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-foundation-model-based-industrial","title":"A Survey on Foundation-Model-Based Industrial Defect Detection","date":"2025-02-26","arxiv_id":"2502.19106","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-yolov7x-based-defect-detection","title":"Improved YOLOv7x-Based Defect Detection Algorithm for Power Equipment","date":"2025-02-25","arxiv_id":"2502.17961","repositories_listed":0,"syntology":null},{"url":null,"slug":"local-flaw-detection-with-adaptive-pyramid","title":"Local Flaw Detection with Adaptive Pyramid Image Fusion Across Spatial Sampling Resolution for SWRs","date":"2025-02-18","arxiv_id":"2502.12512","repositories_listed":0,"syntology":null},{"url":null,"slug":"sem-clip-precise-few-shot-learning-for","title":"SEM-CLIP: Precise Few-Shot Learning for Nanoscale Defect Detection in Scanning Electron Microscope Image","date":"2025-02-15","arxiv_id":"2502.14884","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-yolov7-model-for-insulator-defect","title":"Improved YOLOv7 model for insulator defect detection","date":"2025-02-11","arxiv_id":"2502.07179","repositories_listed":0,"syntology":null},{"url":null,"slug":"yolo-network-for-defect-detection-in-optical","title":"YOLO Network For Defect Detection In Optical lenses","date":"2025-02-11","arxiv_id":"2502.07592","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-appearance-defect-detection-method-for","title":"An Appearance Defect Detection Method for Cigarettes Based on C-CenterNet","date":"2025-02-10","arxiv_id":"2502.06119","repositories_listed":0,"syntology":null},{"url":null,"slug":"terahertz-defect-detection-in-multi-layer","title":"Terahertz Defect Detection in Multi-Layer Materials Using Echo Labeling","date":"2025-02-06","arxiv_id":"2502.04135","repositories_listed":0,"syntology":null},{"url":null,"slug":"spffnet-strip-perception-and-feature-fusion","title":"SPFFNet: Strip Perception and Feature Fusion Spatial Pyramid Pooling for Fabric Defect Detection","date":"2025-02-03","arxiv_id":"2502.01445","repositories_listed":0,"syntology":null},{"url":null,"slug":"surface-defect-identification-using-bayesian","title":"Surface Defect Identification using Bayesian Filtering on a 3D Mesh","date":"2025-01-30","arxiv_id":"2501.18315","repositories_listed":0,"syntology":null},{"url":null,"slug":"effective-defect-detection-using-instance","title":"Effective Defect Detection Using Instance Segmentation for NDI","date":"2025-01-24","arxiv_id":"2501.14149","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-precision-fabric-defect-detection-via","title":"High-Precision Fabric Defect Detection via Adaptive Shape Convolutions and Large Kernel Spatial Modeling","date":"2025-01-24","arxiv_id":"2501.14190","repositories_listed":0,"syntology":null},{"url":null,"slug":"human-ai-collaborative-game-testing-with","title":"Human-AI Collaborative Game Testing with Vision Language Models","date":"2025-01-20","arxiv_id":"2501.11782","repositories_listed":0,"syntology":null},{"url":null,"slug":"patch-aware-vector-quantized-codebook","title":"Patch-aware Vector Quantized Codebook Learning for Unsupervised Visual Defect Detection","date":"2025-01-15","arxiv_id":"2501.09187","repositories_listed":0,"syntology":null},{"url":null,"slug":"defect-detection-network-in-pcb-circuit","title":"Defect Detection Network In PCB Circuit Devices Based on GAN Enhanced YOLOv11","date":"2025-01-12","arxiv_id":"2501.06879","repositories_listed":0,"syntology":null},{"url":null,"slug":"gui-testing-arena-a-unified-benchmark-for","title":"GUI Testing Arena: A Unified Benchmark for Advancing Autonomous GUI Testing Agent","date":"2024-12-24","arxiv_id":"2412.18426","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multimodal-fusion-framework-for-bridge","title":"A Multimodal Fusion Framework for Bridge Defect Detection with Cross-Verification","date":"2024-12-23","arxiv_id":"2412.17968","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-signal-analysis-for-automated","title":"Adaptive Signal Analysis for Automated Subsurface Defect Detection Using Impact Echo in Concrete Slabs","date":"2024-12-23","arxiv_id":"2412.17953","repositories_listed":0,"syntology":null},{"url":null,"slug":"detecting-and-classifying-defective-products","title":"Detecting and Classifying Defective Products in Images Using YOLO","date":"2024-12-22","arxiv_id":"2412.16935","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-reinforcement-learning-based-systems-for","title":"Deep Reinforcement Learning Based Systems for Safety Critical Applications in Aerospace","date":"2024-12-21","arxiv_id":"2412.16489","repositories_listed":0,"syntology":null},{"url":null,"slug":"distributed-intelligent-system-architecture","title":"Distributed Intelligent System Architecture for UAV-Assisted Monitoring of Wind Energy Infrastructure","date":"2024-12-12","arxiv_id":"2412.09387","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-hybrid-framework-for-statistical-feature","title":"A Hybrid Framework for Statistical Feature Selection and Image-Based Noise-Defect Detection","date":"2024-12-11","arxiv_id":"2412.08800","repositories_listed":0,"syntology":null},{"url":null,"slug":"2-5d-super-resolution-approaches-for-x-ray","title":"2.5D Super-Resolution Approaches for X-ray Computed Tomography-based Inspection of Additively Manufactured Parts","date":"2024-12-05","arxiv_id":"2412.04525","repositories_listed":0,"syntology":null},{"url":null,"slug":"hyperdefect-yolo-enhance-yolo-with-hypergraph","title":"HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection","date":"2024-12-05","arxiv_id":"2412.03969","repositories_listed":0,"syntology":null},{"url":null,"slug":"thermal-and-rgb-images-work-better-together","title":"Thermal and RGB Images Work Better Together in Wind Turbine Damage Detection","date":"2024-12-05","arxiv_id":"2412.04114","repositories_listed":0,"syntology":null},{"url":null,"slug":"fab-me-a-vision-state-space-and-attention","title":"Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection","date":"2024-12-04","arxiv_id":"2412.03200","repositories_listed":0,"syntology":null},{"url":null,"slug":"in-situ-melt-pool-characterization-via","title":"In-Situ Melt Pool Characterization via Thermal Imaging for Defect Detection in Directed Energy Deposition Using Vision Transformers","date":"2024-11-18","arxiv_id":"2411.12028","repositories_listed":0,"syntology":null},{"url":null,"slug":"tl-clip-a-power-specific-multimodal-pre","title":"Transmission Line Defect Detection Based on UAV Patrol Images and Vision-language Pretraining","date":"2024-11-18","arxiv_id":"2411.11370","repositories_listed":0,"syntology":null},{"url":null,"slug":"wafer-map-defect-classification-using","title":"Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network","date":"2024-11-17","arxiv_id":"2411.11029","repositories_listed":0,"syntology":null},{"url":null,"slug":"3-dusss-3-dimensional-ultrasonic-self","title":"3-DUSSS: 3-Dimensional Ultrasonic Self Supervised Segmentation","date":"2024-11-12","arxiv_id":"2411.07835","repositories_listed":0,"syntology":null},{"url":null,"slug":"pv-faultnet-optimized-cnn-architecture-to","title":"PV-faultNet: Optimized CNN Architecture to detect defects resulting efficient PV production","date":"2024-11-05","arxiv_id":"2411.02997","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-ai-framework-for-defect-detection-in","title":"Scalable AI Framework for Defect Detection in Metal Additive Manufacturing","date":"2024-11-01","arxiv_id":"2411.00960","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-defect-detection-and-grading-of","title":"Automated Defect Detection and Grading of Piarom Dates Using Deep Learning","date":"2024-10-23","arxiv_id":"2410.18208","repositories_listed":0,"syntology":null},{"url":null,"slug":"integrating-artificial-intelligence-models","title":"Integrating Artificial Intelligence Models and Synthetic Image Data for Enhanced Asset Inspection and Defect Identification","date":"2024-10-15","arxiv_id":"2410.11967","repositories_listed":0,"syntology":null},{"url":null,"slug":"yolo-ela-efficient-local-attention-modeling","title":"YOLO-ELA: Efficient Local Attention Modeling for High-Performance Real-Time Insulator Defect Detection","date":"2024-10-15","arxiv_id":"2410.11727","repositories_listed":0,"syntology":null},{"url":null,"slug":"cbam-swint-bl-small-rail-surface-detect","title":"CBAM-SwinT-BL: Small Rail Surface Defect Detection Method Based on Swin Transformer with Block Level CBAM Enhancement","date":"2024-09-30","arxiv_id":"2409.20113","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparse-modelling-for-feature-learning-in-high","title":"Sparse Modelling for Feature Learning in High Dimensional Data","date":"2024-09-28","arxiv_id":"2409.19361","repositories_listed":0,"syntology":null},{"url":null,"slug":"xai-guided-insulator-anomaly-detection-for","title":"XAI-guided Insulator Anomaly Detection for Imbalanced Datasets","date":"2024-09-25","arxiv_id":"2409.16821","repositories_listed":0,"syntology":null},{"url":null,"slug":"cycle-consistency-uncertainty-estimation-for","title":"Cycle-Consistency Uncertainty Estimation for Visual Prompting based One-Shot Defect Segmentation","date":"2024-09-21","arxiv_id":"2409.13984","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-printed-circuit-board-defect","title":"Enhancing Printed Circuit Board Defect Detection through Ensemble Learning","date":"2024-09-14","arxiv_id":"2409.09555","repositories_listed":0,"syntology":null},{"url":null,"slug":"electron-microscopy-based-automatic-defect","title":"Scanning Electron Microscopy-based Automatic Defect Inspection for Semiconductor Manufacturing: A Systematic Review","date":"2024-09-10","arxiv_id":"2409.06833","repositories_listed":0,"syntology":null},{"url":null,"slug":"texture-ad-an-anomaly-detection-dataset-and","title":"Texture-AD: An Anomaly Detection Dataset and Benchmark for Real Algorithm Development","date":"2024-09-10","arxiv_id":"2409.06367","repositories_listed":0,"syntology":null},{"url":null,"slug":"ddnet-deformable-convolution-and-dense-fpn","title":"DDNet: Deformable Convolution and Dense FPN for Surface Defect Detection in Recycled Books","date":"2024-09-08","arxiv_id":"2409.04958","repositories_listed":0,"syntology":null},{"url":null,"slug":"advancing-sem-based-nano-scale-defect","title":"Advancing SEM Based Nano-Scale Defect Analysis in Semiconductor Manufacturing for Advanced IC Nodes","date":"2024-09-06","arxiv_id":"2409.04310","repositories_listed":0,"syntology":null},{"url":null,"slug":"reinforcement-learning-approach-to-optimizing","title":"Reinforcement Learning Approach to Optimizing Profilometric Sensor Trajectories for Surface Inspection","date":"2024-09-05","arxiv_id":"2409.03429","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-role-of-artificial-intelligence-and","title":"The Role of Artificial Intelligence and Machine Learning in Software Testing","date":"2024-09-04","arxiv_id":"2409.02693","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-welding-defect-detection-using","title":"Unsupervised Welding Defect Detection Using Audio And Video","date":"2024-09-03","arxiv_id":"2409.02290","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-supervised-learning-for-identifying","title":"Self-Supervised Learning for Identifying Defects in Sewer Footage","date":"2024-09-02","arxiv_id":"2409.02140","repositories_listed":0,"syntology":null},{"url":null,"slug":"bring-the-power-of-diffusion-model-to-defect","title":"Bring the Power of Diffusion Model to Defect Detection","date":"2024-08-25","arxiv_id":"2408.13845","repositories_listed":0,"syntology":null},{"url":null,"slug":"unlearning-trojans-in-large-language-models-a","title":"Unlearning Trojans in Large Language Models: A Comparison Between Natural Language and Source Code","date":"2024-08-22","arxiv_id":"2408.12416","repositories_listed":0,"syntology":null},{"url":null,"slug":"irregularity-inspection-using-neural-radiance","title":"Irregularity Inspection using Neural Radiance Field","date":"2024-08-21","arxiv_id":"2408.11251","repositories_listed":0,"syntology":null},{"url":"/paper/self-supervised-iterative-refinement-for","slug":"self-supervised-iterative-refinement-for","title":"Self-Supervised Iterative Refinement for Anomaly Detection in Industrial Quality Control","date":"2024-08-21","arxiv_id":"2408.11561","repositories_listed":0,"syntology":null},{"url":null,"slug":"imbalance-aware-culvert-sewer-defect","title":"Imbalance-Aware Culvert-Sewer Defect Segmentation Using an Enhanced Feature Pyramid Network","date":"2024-08-19","arxiv_id":"2408.10181","repositories_listed":0,"syntology":null},{"url":null,"slug":"source-free-test-time-adaptation-for-online","title":"Source-Free Test-Time Adaptation For Online Surface-Defect Detection","date":"2024-08-18","arxiv_id":"2408.09494","repositories_listed":0,"syntology":null},{"url":null,"slug":"long-working-distance-portable-smartphone","title":"Long working distance portable smartphone microscopy for metallic mesh defect detection","date":"2024-08-10","arxiv_id":"2408.05518","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-visual-cross-modality-knowledge","title":"Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing","date":"2024-08-09","arxiv_id":"2408.05307","repositories_listed":0,"syntology":null},{"url":null,"slug":"eliminating-backdoors-in-neural-code-models","title":"Eliminating Backdoors in Neural Code Models for Secure Code Understanding","date":"2024-08-08","arxiv_id":"2408.04683","repositories_listed":0,"syntology":null},{"url":null,"slug":"statistical-batch-based-bearing-fault","title":"Statistical Batch-Based Bearing Fault Detection","date":"2024-07-24","arxiv_id":"2407.17236","repositories_listed":0,"syntology":null},{"url":null,"slug":"yolo-pdd-a-novel-multi-scale-pcb-defect","title":"YOLO-pdd: A Novel Multi-scale PCB Defect Detection Method Using Deep Representations with Sequential Images","date":"2024-07-22","arxiv_id":"2407.15427","repositories_listed":0,"syntology":null},{"url":null,"slug":"gdds-a-single-domain-generalized-defect","title":"GDDS: A Single Domain Generalized Defect Detection Frame of Open World Scenario using Gather and Distribute Domain-shift Suppression Network","date":"2024-07-18","arxiv_id":"2407.13417","repositories_listed":0,"syntology":null},{"url":null,"slug":"in-situ-infrared-camera-monitoring-for-defect","title":"In-Situ Infrared Camera Monitoring for Defect and Anomaly Detection in Laser Powder Bed Fusion: Calibration, Data Mapping, and Feature Extraction","date":"2024-07-17","arxiv_id":"2407.12682","repositories_listed":0,"syntology":null},{"url":null,"slug":"fabgpt-an-efficient-large-multimodal-model","title":"FabGPT: An Efficient Large Multimodal Model for Complex Wafer Defect Knowledge Queries","date":"2024-07-15","arxiv_id":"2407.10810","repositories_listed":0,"syntology":null},{"url":null,"slug":"unified-anomaly-detection-methods-on-edge","title":"Unified Anomaly Detection methods on Edge Device using Knowledge Distillation and Quantization","date":"2024-07-03","arxiv_id":"2407.02968","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-reducing-data-acquisition-and","title":"Towards Reducing Data Acquisition and Labeling for Defect Detection using Simulated Data","date":"2024-06-27","arxiv_id":"2406.19175","repositories_listed":0,"syntology":null},{"url":null,"slug":"faster-metallic-surface-defect-detection","title":"Faster Metallic Surface Defect Detection Using Deep Learning with Channel Shuffling","date":"2024-06-19","arxiv_id":"2406.14582","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-survey-on-machine-learning-1","title":"A Comprehensive Survey on Machine Learning Driven Material Defect Detection","date":"2024-06-12","arxiv_id":"2406.07880","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-prisma-driven-systematic-review-of-publicly","title":"A PRISMA Driven Systematic Review of Publicly Available Datasets for Benchmark and Model Developments for Industrial Defect Detection","date":"2024-06-11","arxiv_id":"2406.07694","repositories_listed":0,"syntology":null},{"url":null,"slug":"global-regularized-neighborhood-regression","title":"Global-Regularized Neighborhood Regression for Efficient Zero-Shot Texture Anomaly Detection","date":"2024-06-11","arxiv_id":"2406.07333","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-deep-learning-augmented-stand-off-radar","title":"A Deep Learning-Augmented Stand-off Radar Scheme for Rapidly Detecting Tree Defects","date":"2024-06-08","arxiv_id":"2406.05389","repositories_listed":0,"syntology":null},{"url":"/paper/sam-lad-segment-anything-model-meets-zero","slug":"sam-lad-segment-anything-model-meets-zero","title":"SAM-LAD: Segment Anything Model Meets Zero-Shot Logic Anomaly Detection","date":"2024-06-02","arxiv_id":"2406.00625","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-study-on-unsupervised-anomaly-detection-and","title":"A Study on Unsupervised Anomaly Detection and Defect Localization using Generative Model in Ultrasonic Non-Destructive Testing","date":"2024-05-26","arxiv_id":"2405.16580","repositories_listed":0,"syntology":null},{"url":null,"slug":"memorymamba-memory-augmented-state-space","title":"MemoryMamba: Memory-Augmented State Space Model for Defect Recognition","date":"2024-05-06","arxiv_id":"2405.03673","repositories_listed":0,"syntology":null},{"url":null,"slug":"defect-localization-using-region-of-interest","title":"Defect Localization Using Region of Interest and Histogram-Based Enhancement Approaches in 3D-Printing","date":"2024-04-25","arxiv_id":"2404.17015","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-for-pre-post-flight-uav","title":"Machine Learning for Pre/Post Flight UAV Rotor Defect Detection Using Vibration Analysis","date":"2024-04-24","arxiv_id":"2404.15880","repositories_listed":0,"syntology":null},{"url":null,"slug":"in-situ-process-monitoring-and-adaptive","title":"In-situ process monitoring and adaptive quality enhancement in laser additive manufacturing: a critical review","date":"2024-04-21","arxiv_id":"2404.13673","repositories_listed":0,"syntology":null},{"url":null,"slug":"carcassformer-an-end-to-end-transformer-based","title":"CarcassFormer: An End-to-end Transformer-based Framework for Simultaneous Localization, Segmentation and Classification of Poultry Carcass Defect","date":"2024-04-17","arxiv_id":"2404.11429","repositories_listed":0,"syntology":null},{"url":null,"slug":"ai-guided-defect-detection-techniques-to","title":"AI-Guided Defect Detection Techniques to Model Single Crystal Diamond Growth","date":"2024-04-10","arxiv_id":"2404.07306","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-defect-detection-in-sewer-network","title":"Automatic Defect Detection in Sewer Network Using Deep Learning Based Object Detector","date":"2024-04-09","arxiv_id":"2404.06219","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-improved-semiconductor-defect","title":"Towards Improved Semiconductor Defect Inspection for high-NA EUVL based on SEMI-SuperYOLO-NAS","date":"2024-04-08","arxiv_id":"2404.05862","repositories_listed":0,"syntology":null},{"url":null,"slug":"stochastic-geometry-models-for-texture","title":"Stochastic Geometry Models for Texture Synthesis of Machined Metallic Surfaces: Sandblasting and Milling","date":"2024-03-20","arxiv_id":"2403.13439","repositories_listed":0,"syntology":null},{"url":null,"slug":"ocr-is-all-you-need-importing-multi-modality","title":"OCR is All you need: Importing Multi-Modality into Image-based Defect Detection System","date":"2024-03-18","arxiv_id":"2403.11536","repositories_listed":0,"syntology":null},{"url":null,"slug":"lerenet-eliminating-intra-class-differences","title":"LERENet: Eliminating Intra-class Differences for Metal Surface Defect Few-shot Semantic Segmentation","date":"2024-03-17","arxiv_id":"2403.11122","repositories_listed":0,"syntology":null},{"url":null,"slug":"open-stamped-parts-dataset","title":"Open Stamped Parts Dataset","date":"2024-03-15","arxiv_id":"2403.10369","repositories_listed":0,"syntology":null},{"url":null,"slug":"achieving-pareto-optimality-using-efficient","title":"Achieving Pareto Optimality using Efficient Parameter Reduction for DNNs in Resource-Constrained Edge Environment","date":"2024-03-14","arxiv_id":"2403.10569","repositories_listed":0,"syntology":null}],"record_sha256":"1da105f151aab49d9df9c7384f0c008c9d0a93180236b0078df1d8497005ab7e","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}