Del i serien Springer Series on Challenges in Machine Learning

Inpainting and Denoising Challenges

Häftad, Engelska, 2020

AvSergio Escalera,Stephane Ayache,Jun Wan,Meysam Madadi,Umut Güçlü,Xavier Baró

719 kr

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This volume starts with a wide review on image denoising, retracing and comparing various methods from the pioneer signal processing methods, to machine learning approaches with sparse and low-rank models, and recent deep learning architectures with autoencoders and variants.

Produktinformation

Utgivningsdatum2020-10-17
Mått155 x 235 x 9 mm
Vikt242 g
FormatHäftad
SpråkEngelska
SerieSpringer Series on Challenges in Machine Learning
Antal sidor144
FörlagSpringer Nature Switzerland AG
ISBN9783030256166

Tillhör följande kategorier

Systemvetenskap och AI inom Data och IT

1. A Brief Review of Image Denoising Algorithms and Beyond.- 2. ChaLearn Looking at People: Inpainting and Denoising Challenges.- 3. U-Finger: Multi-Scale Dilated Convolutional Network for Fingerprint Image Denoising and Inpainting.- 4. FPD-M-net: Fingerprint Image Denoising and Inpainting Using M-Net Based Convolutional Neural Networks.- 5. Iterative Application of Autoencoders for Video Inpainting and Fingerprint Denoising.- 6. Video DeCaptioning using U-Net with Stacked Dilated Convolutional Layers.- 7. Joint Caption Detection and Inpainting using Generative Network.- 8. Generative Image Inpainting for Person Pose Generation.- 9. Person Inpainting with Generative Adversarial Networks.- 10. Road Layout Understanding by Generative Adversarial Inpainting.- 11. Photo-realistic and Robust Inpainting of Faces using Refinement GANs.