Training RNNs as fast as CNNs: introduces new layer type with better parallelism, similar quality across many tasks https://arxiv.org/abs/1709.02755
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Low-Flying Autonomous Drone Trail Navigation. Object avoidance & trail navigation with onboard computer vision https://arxiv.org/abs/1705.02550
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Efficient Methods and HW for Deep Learning
S. Han, Invited, Stanford CS231n, 2017 https://www.youtube.com/watch?v=eZdOkDtYMoo
PDF http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture15.pdf
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The Conference on Empirical Methods in Natural Language Processing (EMNLP), includes research that will help all regions videos http://goo.gl/eBp92s
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Researchers from Korea presented a #deeplearning-based approach to detect diseases and pests in tomato plants http://www.mdpi.com/1424-8220/17/9/2022
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#Breaking_news :Should artificial intelligence be regulated? Answers by Andrew Ng http://goo.gl/gLFrSg
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GANs comparison without cherry-picking : BEGAN generates the best examples while WGAN does not give impressive ones http://goo.gl/Dzu5Cf
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#Lecture for CMU CS, Neural Networks for #NLP 2017
http://goo.gl/QyDGbo
#MachineLearning
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Recommending this if you want to get into med #Deep_Learning in #Medical_Image_Analysis
1https://arxiv.org/abs/1708.08987
2 https://arxiv.org/abs/1702.05747
3 https://buff.ly/2w3iHa8
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The Conference on Empirical Methods in Natural Language Processing (EMNLP), includes research that will help all regions videos http://goo.gl/eBp92s
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Researchers from Korea presented a #deeplearning-based approach to detect diseases and pests in tomato plants http://www.mdpi.com/1424-8220/17/9/2022
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#Lecture for CMU CS, Neural Networks for #NLP 2017
http://goo.gl/QyDGbo
#MachineLearning
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#Dataset: 230,000 3D facial landmarks. We are quite close to solving the 2D & 3D Face Alignment problem. https://www.adrianbulat.com/face-alignment
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Recommending this if you want to get into med #Deep_Learning in #Medical_Image_Analysis
1https://arxiv.org/abs/1708.08987
2 https://arxiv.org/abs/1702.05747
3 https://buff.ly/2w3iHa8
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