most citedDeep Anomaly Detection on Tennessee Eastman Process Data

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.AI2024

AI-based Anomaly Detection for Clinical-Grade Histopathological Diagnostics

Jonas Dippel, Niklas Prenißl, Julius Hense +10

While previous studies have demonstrated the potential of AI to diagnose diseases in imaging data, clinical implementation is still lagging behind. This is partly because AI models…

cs.LG2023★ 1 cited

Deep Anomaly Detection on Tennessee Eastman Process Data

Fabian Hartung, Billy Joe Franks, Tobias Michels +15

This paper provides the first comprehensive evaluation and analysis of modern (deep-learning) unsupervised anomaly detection methods for chemical process data. We focus on the Tenn…