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Recent Studies from Rice University Add New Data to Networks (Rate-optimal Denoising With Deep Neural Networks)

机译:莱斯大学最近的研究从添加新数据网络(Rate-optimal去噪与深神经网络)

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摘要

By a News Reporter-Staff News Editor at Network Daily News – Investigators publish new report on Networks. According to news reporting out of Houston, Texas, by NewsRx editors, research stated, “Deep neural networks provide state-of-the-art performance for image denoising, where the goal is to recover a near noise-free image from a noisy observation. The underlying principle is that neural networks trained on large data sets have empirically been shown to be able to generate natural images well from a low-dimensional latent representation of the image.”
机译:由一个新闻记者在网络新闻编辑每日新闻,调查人员发布的新报告网络。休斯顿,德克萨斯州,NewsRx编辑、研究说,“深层神经网络提供的先进的图像去噪的性能,无噪声的附近的目标是恢复吗从嘈杂的观察图像。原则是,神经网络训练大型数据集有经验了能够产生自然图像从一个低维的潜在表示形象。”

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