1 citations · 1 across the 4 of their papers we have counts for
5 papers
A Data-Driven Framework for Unsupervised Monitoring of Transmission Systems Using End-of-Line Testing Data: A Case Study at Ford Motor Company
Mohammad N. Bisheh, Mehrdad Moradi, Parinaz Farajiparvar +6
Sensing technologies have advanced rapidly across industries ranging from energy to automotive manufacturing. These systems generate high-dimensional (HD) data characterized by com…
Flow Mismatching: Unsupervised Anomaly Detection via Velocity Discrepancies in Flow Matching Models
Shengzhe Chen, Mehrdad Moradi, Kamran Paynabar +1
We propose Flow Mismatching, an unsupervised anomaly detection method that deliberately avoids reconstruction-based paradigms. Instead, we treat flow matching as geometric dynamics…
A Single Image Is All You Need: Zero-Shot Anomaly Localization Without Training Data
Mehrdad Moradi, Shengzhe Chen, Hao Yan +1
Anomaly detection in images is typically addressed by learning from collections of training data or relying on reference samples. In many real-world scenarios, however, such traini…
RDDPM: Robust Denoising Diffusion Probabilistic Model for Unsupervised Anomaly Segmentation
Mehrdad Moradi, Kamran Paynabar
Recent advancements in diffusion models have demonstrated significant success in unsupervised anomaly segmentation. For anomaly segmentation, these models are first trained on norm…
Single-Step Reconstruction-Free Anomaly Detection and Segmentation via Diffusion Models
Mehrdad Moradi, Marco Grasso, Bianca Maria Colosimo +1
Generative models have demonstrated significant success in anomaly detection and segmentation over the past decade. Recently, diffusion models have emerged as a powerful alternativ…