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Shakeel Mahate
1,216 followers -
Software geek
Software geek

1,216 followers
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Pursuing video understanding at YouTube-8M’s scale would normally require a petabyte of video storage and dozens of CPU-years worth of processing. To make the dataset useful to researchers and students with limited computational resources, we pre-processed the videos and extracted frame-level features using a state-of-the-art deep learning model--the publicly available Inception-V3 image annotation model trained on ImageNet. These features are extracted at 1 frame-per-second temporal resolution, from 1.9 billion video frames, and are further compressed to fit on a single commodity hard disk (less than 1.5 TB). This makes it possible to download this dataset and train a baseline TensorFlow model at full scale on a single GPU in less than a day!

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Fall harvests at NCSU
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Nice summary of 25 years of Linux

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Pomegranates from our garden
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Muscadine grapes from our garden
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