About: Deep image prior

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Deep image prior is a type of convolutional neural network used to enhance a given image with no prior training data other than the image itself.A neural network is randomly initialized and used as prior to solve inverse problems such as noise reduction, super-resolution, and inpainting. Image statistics are captured by the structure of a convolutional image generator rather than by any previously learned capabilities.

Property	Value
dbo:abstract	Deep image prior is a type of convolutional neural network used to enhance a given image with no prior training data other than the image itself.A neural network is randomly initialized and used as prior to solve inverse problems such as noise reduction, super-resolution, and inpainting. Image statistics are captured by the structure of a convolutional image generator rather than by any previously learned capabilities. (en)
dbo:wikiPageExternalLink	https://github.com/DmitryUlyanov/deep-image-prior https://github.com/beala/deep-image-prior-tensorflow https://github.com/rodgzilla/machine_learning_denoising
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dbo:wikiPageWikiLink	dbr:Python_(programming_language) dbr:Inpainting dbr:Inverse_problem dbr:GPLv3 dbr:Creative_Commons dbr:Mathematical_optimization dbr:Gradient_descent dbr:Convolutional_neural_network dbr:Decimation_(signal_processing) dbr:Hadamard_product_(matrices) dbr:Lanczos_resampling dbr:Local_optimum dbr:Noise_reduction dbr:Regularization_(mathematics) dbr:Tensor dbr:TensorFlow dbr:Keras dbr:Super-resolution dbc:Deep_learning dbr:Apache_2.0 dbr:Inverse_problems dbr:Overfitting dbr:Deep_neural_networks dbr:Denoising dbr:PyTorch_0.4.0
dbp:wikiPageUsesTemplate	dbt:Cite_arXiv dbt:Multiple_issues dbt:Notability dbt:One_source dbt:Technical dbt:Noise
dct:subject	dbc:Deep_learning
rdfs:comment	Deep image prior is a type of convolutional neural network used to enhance a given image with no prior training data other than the image itself.A neural network is randomly initialized and used as prior to solve inverse problems such as noise reduction, super-resolution, and inpainting. Image statistics are captured by the structure of a convolutional image generator rather than by any previously learned capabilities. (en)
rdfs:label	Deep image prior (en)
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