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iceflame co
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Improving  video thumbnails with DNN

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Accepted to ICCV 2015 (oral). We solve MRF by proposing a Convolutional Neural Network (CNN), namely Deep Parsing Network (DPN), which enables deterministic end-to-end computation in a single forward pass.

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Deep learning has shown remarkable success on some of the world’s most difficult computer science challenges. Today on the Google Research blog we go into how Long Short-term Memory Recurrent Neural Networks (LSTM RNNs) are being used to improve Google Voice transcription. 

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We had been quietly working on Mandarin Chinese speech recognition since February, and just unveiled the system this week. Because Chinese is a tonal language---the same sound pronounced with different inflections has dramatically different meanings---Chinese is hard for non-native speakers (who often don't even hear the tones) to master. Many researchers therefore asked if we had to do a lot of work to adapt our English speech system to Chinese. With Deep Speech, we found end-to-end learning was able to figure out the tones by itself. As usual, the formula for success was simply SCALE: Lots of data, and a huge network. The ease of adapting Deep Speech to Chinese also makes me optimistic about new languages. In this article, Awni Hannun and Bryan Catanzaro share lots of details. Go to: https://medium.com/s-c-a-l-e/how-baidu-mastered-mandarin-with-deep-learning-and-lots-of-data-1d94032564a5

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I'm enjoying this new G+ layout. Here's another Tall Photo I hadn't shared before. Taken in Sydney, Australia in January.  This dramatic sunset was going off and I was scrambling trying to find the best spot to take a photo. Fun times!  

Tomorrow I'm headed to South Korea for two nights. Does anyone have any suggestions on cool buildings or landscapes to photograph for my two quick nights there in Seoul? 
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