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英文字典中文字典相关资料:


  • Super Resolution - DeepAI
    The Super Resolution API uses machine learning to clarify, sharpen, and upscale the photo without losing its content and defining characteristics Blurry images are unfortunately common and are a problem for professionals and hobbyists alike
  • DeepAI Docs
    Super Resolution: The Super Resolution API is designed to upscale images without losing the original content It uses machine learning to improve the quality of images, making them sharper and correcting any blurriness
  • Upscale Images With DeepAI’s Super Resolution API
    In this article, we are going to implement the “Super Resolution API” using Delphi This API uses machine learning to clean, sharp and upscale photos with out losing the original content
  • Explorable Super Resolution - DeepAI
    In this paper, we introduce the task of explorable super resolution We propose a framework comprising a graphical user interface with a neural network backend, allowing editing the SR output so as to explore the abundance of plausible HR explanations to the LR input
  • Super-Resolution via Deep Learning | DeepAI
    We focus on the three important aspects of multimedia - namely image, video and multi-dimensions, especially depth maps In each case, first relevant benchmarks are introduced in the form of datasets and state of the art SR methods, excluding deep learning
  • Super-Resolution Neural Operator | DeepAI
    We propose Super-resolution Neural Operator (SRNO), a deep operator learning framework that can resolve high-resolution (HR) images at arbitrary scales from the low-resolution (LR) counterparts
  • Deep Networks for Image and Video Super-Resolution | DeepAI
    To enable super-resolution for multiple factors, we propose a scale-recurrent framework which reutilizes the filters learnt for lower scale factors recursively for higher factors This leads to improved performance and promotes parametric efficiency for higher factors
  • Image Super-Resolution With Deep Variational Autoencoders | DeepAI
    Image super-resolution (SR) techniques are used to generate a high-resolution image from a low-resolution image Until now, deep generative models such as autoregressive models and Generative Adversarial Networks (GANs) have proven to be effective at modelling high-resolution images
  • Image Super-Resolution with Deep Dictionary | DeepAI
    We propose an end-to-end super-resolution network with a deep dictionary (SRDD), where a high-resolution dictionary is explicitly learned without sacrificing the advantages of deep learning
  • One-to-many Approach for Improving Super-Resolution | DeepAI
    Super-resolution (SR) is a one-to-many task with multiple possible solutions However, previous works were not concerned about this characteristic For a one-to-many pipeline, the generator should be able to generate multiple estimates of the reconstruction, and not be penalized for generating similar and equally realistic images





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