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Found 4 papers, 1 papers with code
Do LLMs Understand Visual Anomalies? Uncovering LLM Capabilities in Zero-shot Anomaly Detection
However, existing approaches depend on static anomaly prompts that are prone to cross-semantic ambiguity, and prioritize global image-level representations over crucial local pixel-level image-to-text alignment that is necessary for accurate anomaly localization.
METER: A Dynamic Concept Adaptation Framework for Online Anomaly Detection
Real-time analytics and decision-making require online anomaly detection (OAD) to handle drifts in data streams efficiently and effectively.
Flexible Job Shop Scheduling via Dual Attention Network Based Reinforcement Learning
The complex relationships between operations and machines are represented precisely and concisely, for which a dual-attention network (DAN) comprising several interconnected operation message attention blocks and machine message attention blocks is proposed.
End-to-End Code-Switching ASR for Low-Resourced Language Pairs
In this work, we describe an E2E ASR pipeline for the recognition of CS speech in which a low-resourced language is mixed with a high resourced language.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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