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SOTA
Anomalieerkennung
Anomaly Detection On Fashion Mnist
Anomaly Detection On Fashion Mnist
Metriken
ROC AUC
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
ROC AUC
Paper Title
Repository
Self-Supervised DeepSVDD
84.8
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation
P-KDGAN
0.9293
P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection
-
IGD (scratch)
92.01
Deep One-Class Classification via Interpolated Gaussian Descriptor
Self-Supervised One-class SVM, RBF kernel
92.8
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation
GAN based Anomaly Detection in Imbalance Problems
98.6
GAN-based Anomaly Detection in Imbalance Problems
-
Shell-based Anomaly (supervised)
92.1
Shell Theory: A Statistical Model of Reality
IGD (pre-trained ImageNet)
93.57
Deep One-Class Classification via Interpolated Gaussian Descriptor
PANDA-OE
91.8
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation
Reverse Distillation
95.0
Anomaly Detection via Reverse Distillation from One-Class Embedding
PANDA
95.6
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation
IGD (pre-trained SSL)
94.41
Deep One-Class Classification via Interpolated Gaussian Descriptor
DASVDD
92.6
DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly Detection
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