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Photo by Jon Tyson on Unsplash

One of the fundamental challenges in the field of image processing and computer vision is image denoising, where the underlying goal is to estimate the original image by suppressing noise from a noise-contaminated version of the image.

Contents :

  1. Business Problem
  2. Use of Deep Learning
  3. Source of Data
  4. Existing Approaches
  5. Ridnet
  6. First Cut Solution
  7. Implementation
  8. References
  9. Github Repo
  10. Linkedin profile

1. Business Problem

Image noise may be caused by different intrinsic (i.e. sensor) and extrinsic (i.e. environment) conditions which are often not possible to avoid in practical situations.

Therefore, image denoising plays an important role in a wide range of applications such as image restoration, visual tracking, image registration, image segmentation, and image classification, where obtaining the original image content is crucial for strong performance. …


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Photo by Clay Banks on Unsplash

Instead of waking to overlooked “Do not disturb” signs, Airbnb travelers find themselves rising with the birds in a whimsical treehouse, having their morning coffee on the deck of a houseboat, or cooking a shared regional breakfast with their hosts.

New users on Airbnb can book a place to stay in 34,000+ cities across 190+ countries. By accurately predicting where a new user will book their first travel experience, Airbnb can share more personalized content with their community, decrease the average time to first booking, and better forecast demand.

In this kaggle competition, Airbnb challenges you to predict in which country a new user will make his or her first booking. …

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