Results 31 to 40 of about 1,132,388 (176)
List-Mode PET Image Reconstruction Using Deep Image Prior
IEEE Transactions on Medical Imaging, 2023 List-mode positron emission tomography (PET) image reconstruction is an important tool for PET scanners with many lines-of-response and additional information such as time-of-flight and depth-of-interaction. Deep learning is one possible solution to enhance the quality of PET image reconstruction. However, the application of deep learning techniques to
Kibo Ote +4 more
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Deep learning-based image recognition for autonomous driving
IATSS Research, 2019 Various image recognition tasks were handled in the image recognition field prior to 2010 by combining image local features manually designed by researchers (called handcrafted features) and machine learning method. After entering the 2010, However, many
Hironobu Fujiyoshi +2 more
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A Single Image Deep Learning Approach to Restoration of Corrupted Landsat-7 Satellite Images
Sensors, 2022 Remote sensing is increasingly recognized as a convenient tool with a wide variety of uses in agriculture. Landsat-7 has supplied multi-spectral imagery of the Earth’s surface for more than 4 years and has become an important data source for a large ...
Anna Petrovskaia +2 more
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Solar Speckle Image Deblurring With Deep Prior Constraint Based on Regularization
IEEE Access, 2022 The solar speckle image has the characteristics with single features, more noise, and blurred local details. Most of the existing deep learning deblurring methods for solar speckle images have some problems, such as high-frequency loss, artifact ...
Yahui Jin +5 more
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Anchored neighborhood deep network for single-image super-resolution
EURASIP Journal on Image and Video Processing, 2018 Real-time image and video processing is a challenging problem in smart surveillance applications. It is necessary to trade off between high frame rate and high resolution to meet the limited bandwidth requirement in many specific applications.
Wuzhen Shi +4 more
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Dynamic PET Image Denoising Using Deep Image Prior Combined With Regularization by Denoising
IEEE Access, 2021 The quantitative accuracy of positron emission tomography (PET) is affected by several factors, including the intrinsic resolution of the imaging system and inherently noisy data, which result in a low signal-to-noise ratio (SNR) of PET image. To address
Hao Sun +5 more
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Weak deep priors for seismic imaging [PDF]
SEG Technical Program Expanded Abstracts 2020, 2020 Incorporating prior knowledge on model unknowns of interest is essential when dealing with ill-posed inverse problems due to the nonuniqueness of the solution and data noise. Unfortunately, it is not trivial to fully describe our priors in a convenient and analytical way.
Siahkoohi, Ali +2 more
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Image Denoising Using Nonlocal Regularized Deep Image Prior [PDF]
Symmetry, 2021 Deep neural networks have shown great potential in various low-level vision tasks, leading to several state-of-the-art image denoising techniques. Training a deep neural network in a supervised fashion usually requires the collection of a great number of examples and the consumption of a significant amount of time.
Zhonghua Xie +3 more
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Hyperspectral Image Mixed Noise Removal Using Subspace Representation and Deep CNN Image Prior
Remote Sensing, 2021 The ever-increasing spectral resolution of hyperspectral images (HSIs) is often obtained at the cost of a decrease in the signal-to-noise ratio (SNR) of the measurements.
Lina Zhuang, Michael K. Ng, Xiyou Fu
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Time-Dependent Deep Image Prior for Dynamic MRI [PDF]
IEEE Transactions on Medical Imaging, 2021 We propose a novel unsupervised deep-learning-based algorithm for dynamic magnetic resonance imaging (MRI) reconstruction. Dynamic MRI requires rapid data acquisition for the study of moving organs such as the heart. Existing reconstruction methods suffer from restrictions either in the model design or in the absence of ground-truth data, resulting in ...
Jaejun Yoo +5 more
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