Inpainting and Denoising Challenges

Inbunden, Engelska, 2019

Del i serien Springer Series on Challenges in Machine Learning

550 kr

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Beskrivning

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

Utgivningsdatum:2019-10-17
Mått:155 x 235 x 14 mm
Vikt:401 g
Format:Inbunden
Språk:Engelska
Serie:Springer Series on Challenges in Machine Learning
Antal sidor:144
Förlag:Springer Nature Switzerland AG
ISBN:9783030256135

Utforska kategorier

Systemvetenskap och AI inom Data och IT

Innehållsförteckning

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.