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RADIOlogy: A Single-Pass Approach to Training-Free Zero-Shot Anomaly Detection
Current zero-shot anomaly detection methods often rely on complex prompt-learning techniques or computationally expensive sliding-window strategies to achieve fine-grained visual alignment to detect small-scale anomalies. This reliance stems from the fundamental limitation of standard CLIP architect
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