الرئيسية الأخبار الأوراق البحثية الدروس مجموعات البيانات الموسوعة SOTA نماذج LLM لوحة الأداء GPU الفعاليات

العربية

Anomaly Detection On Btad

المقاييس

Detection AUROC

Segmentation AUPRO

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

اسم النموذج	Detection AUROC	Segmentation AUPRO	Paper Title	Repository
ReConPatch WRN-50	95.8	97.5	ReConPatch : Contrastive Patch Representation Learning for Industrial Anomaly Detection	-
PatchSVDD	-	-	Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation	-
CPR	94.8	85.1	Target before Shooting: Accurate Anomaly Detection and Localization under One Millisecond via Cascade Patch Retrieval	-
MuSc (zero-shot)	96.16	83.43	MuSc: Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images	-
RealNet	96.1	-	RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection	-
FastFlow+AltUB	-	-	AltUB: Alternating Training Method to Update Base Distribution of Normalizing Flow for Anomaly Detection	-
PNI	-	-	PNI : Industrial Anomaly Detection using Position and Neighborhood Information
URD	93.9	78.5	Unlocking the Potential of Reverse Distillation for Anomaly Detection	-
AD-CLSCNFs	95.93	72.77	Anomaly Detection Using Normalizing Flow-Based Density Estimation and Synthetic Defect Classification
WeakREST-Un	94.4	84.9	Industrial Anomaly Detection and Localization Using Weakly-Supervised Residual Transformers	-
VT-ADL	-	-	VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization	-
D3AD	95.2	83.2	Dynamic Addition of Noise in a Diffusion Model for Anomaly Detection	-
Reverse Distillation ++	95.63	-	Revisiting Reverse Distillation for Anomaly Detection
PyramidFlow (Res18)	95.8	-	PyramidFlow: High-Resolution Defect Contrastive Localization using Pyramid Normalizing Flow	-

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