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denoising convolutional neural network

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8月26日
10:31
10:31官方账号arXiv cs.LG@Weimin Zhou
This paper introduces a score-based ideal observer (SIO) using a denoising convolutional neural network for signal-known-exactly detection tasks. The SIO approximates the Bayesian Ideal Observer (IO) performance without per-image posterior sampling or signal-specific retraining. Numerical studies on a stochastic lumpy-background model show promising results.
论文score-based generative modelingsignal detectionBayesian Ideal Observer
推荐理由：This paper presents a novel approach to signal detection that approximates the IO performance without the need for extensive retraining, making it a valuable read for those interested in signal detection and generative modeling.
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