DiAD: A Diffusion-based Framework for Multi-class Anomaly Detection.
Haoyang HeJiangning ZhangHongxu ChenXuhai ChenZhishan LiXu ChenYabiao WangChengjie WangLei XiePublished in: CoRR (2023)
Keyphrases
- machine learning
- multi class
- anomaly detection
- support vector machine
- intrusion detection
- error correcting output codes
- detecting anomalies
- network traffic
- cost sensitive
- multiple classes
- network intrusion detection
- computer vision
- intrusion detection system
- multi class classification
- multi task
- probabilistic model
- network anomaly detection
- neural network
- supervised learning
- object detection
- pairwise
- binary classification
- text mining
- decision trees
- association rules
- one class support vector machines
- multi class boosting