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New theory explores deep learning for speckle noise in imaging

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a minimax theory for likelihood-based deep learning to address speckle noise in imaging modalities like synthetic aperture radar and optical coherence tomography. This new framework handles both multiplicative speckle noise and additive Gaussian noise, accommodating low-dimensional and sparse high-dimensional features. The study establishes finite-sample upper bounds and derives minimax lower bounds, showing that the intrinsic difficulty of estimation is largely unchanged compared to models with only additive Gaussian noise. AI

IMPACT Provides a theoretical foundation for applying deep learning to challenging noise models in scientific imaging.

RANK_REASON The cluster contains an academic paper detailing a new theoretical framework for deep learning in a specific statistical context.

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New theory explores deep learning for speckle noise in imaging

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The cluster contains an academic paper detailing a new theoretical framework for deep learning in a specific statistical context.
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COVERAGE [2]

  1. arXiv stat.ML TIER_1 English(EN) · Soham Jana ·

    Minimax Theory of Likelihood-Based Deep Learning for Speckle Regression

    arXiv:2607.14064v1 Announce Type: cross Abstract: Speckle noise is a multiplicative noise commonly encountered in coherent imaging modalities such as synthetic aperture radar, optical coherence tomography, and digital holography. Although deep learning methods, in practice, have …

  2. arXiv stat.ML TIER_1 English(EN) · Soham Jana ·

    Minimax Theory of Likelihood-Based Deep Learning for Speckle Regression

    Speckle noise is a multiplicative noise commonly encountered in coherent imaging modalities such as synthetic aperture radar, optical coherence tomography, and digital holography. Although deep learning methods, in practice, have achieved state-of-the-art performance for speckle …

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