Self-Supervised Photo Upsampling, Fast & High-Quality E2E Text-to-Speech & Artificial Intelligence in Indian Railways in today’s Data Science Daily 📰
Given a low-resolution input image, PULSE searches the outputs of a generative model (here, StyleGAN) for high-resolution images that are perceptually realistic and downscale correctly.
GitHub: https://github.com/adamian98/pulse
Paper link: https://arxiv.org/pdf/2003.03808.pdf
This is a PyTorch implementation of Microsoft’s text-to-speech system FastSpeech 2: Fast and High-Quality End-to-End Text to Speech. This project is based on xcmyz’s implementation of FastSpeech.
👉 https://fastspeech2.github.io/fastspeech2
GitHub: https://github.com/ming024/FastSpeech2
Spread across a whopping 1,15,000 kilometres, the Indian Railways consists of a massive network of tracks running from everywhere to everywhere.
The Indian Railways forms the world’s second-largest railway network. Thus, one can imagine the kind of cooperation that is necessary from the different departments involved, for the system to function daily.
The purpose of any technology is to simplify manual work — more accurate work in less time. Considering the scale of operations of the Indian Railways, there are several areas that can benefit from artificial intelligence.
Here’s an article on areas where the use of AI in Indian Railways would lead to smoother operations 👉 https://data-flair.training/news/artificial-intelligence-in-indian-railways
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