HDR for UE4

HDR, GameWorks, GameWorks Expert Developer

Evan Hart, posted Aug 25 2016

As you may have read in our last post, there are several things that you may want to do to provide a great HDR experience from your game. To help demonstrate these things, we went and plumbed them into the Unreal Engine. This is all available on GitHub right now for those with UE4 access.

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GPU Technology Conference 2017: Call for Submissions Now Open

Events, News, Research, Automotive, Higher Education / Academia, Image Recognition, Machine Learning & Artificial Intelligence, Robotics, Speech & Audio Processing, Virtual Reality

Nadeem Mohammad, posted Aug 24 2016

Take part in the world’s top GPU developer event May 8 -11, 2017 in Silicon Valley where artificial intelligence, virtual reality and autonomous vehicles will take center stage. GTC 2017 provides developers and thought leaders with the opportunity to share their work with thousands of the world’s brightest minds. The 2016 event had more than

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Mobile App Helps Find Furniture You See in the Real World

Research, Cloud, cuDNN, GeForce, Higher Education / Academia, Image Processing, Machine Learning & Artificial Intelligence, Media & Entertainment

Nadeem Mohammad, posted Aug 23 2016

Take a photo of a chair and a new mobile app will tell you where to buy it, and show you pictures of how it will look in various rooms. “It seems a lot of people want to buy things they see in someone else’s home or in a photo, but they don’t know where

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Share Your Science: Using Deep Learning to Automatically Detect Geophysical Features

Research, CUDA, cuDNN, Development Tools & Libraries, Higher Education / Academia, Machine Learning & Artificial Intelligence, Oil & Gas, Share Your Science, Tesla

Nadeem Mohammad, posted Aug 19 2016

Chiyuan Zhang, PhD student at MIT talks about his joint project with Shell using GPUs and deep learning to automatically detect subsurface faults from seismic traces for oil and gas exploration. Using a Tesla K80 GPU, CUDA, cuBLAS and the cuDNN-accelerated Mocha.jl deep learning framework, the researchers were able to speed-up up their experiments nearly

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Deep Learning and Satellite Data Helping Map Poverty

Research, cuDNN, GeForce, Higher Education / Academia, Image Recognition, Machine Learning & Artificial Intelligence, Tesla

Nadeem Mohammad, posted Aug 18 2016

Stanford scientists developed a solution combining high-resolution satellite imagery with deep learning to accurately predict poverty levels at the village level. Using TITAN X and Tesla K40 GPUs with the cuDNN-accelerated Caffe and Tensorflow deep learning frameworks to train their convolutional neural networks, the researchers used the “nightlight” satellite data to identify features in the

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