bringing efficient deep learning to Advanced Driver Assistance Systems and Autonomous Vehicles. "Are We Short of Deep Learning Experts?". Tran,. Unfortunately, these two methods cannot be combined.
Forrest Iandola is an American computer scientist and entrepreneur. While a gradua te student at University of California, Berkeley, Iandola developed.
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"Deep Learning Reading Group: SqueezeNet". Gao,. At DeepScale, we spent a lot of time optimizing our product-market fit, and it has paid off. Deep Compression, arxiv:1510.00149, 2015. 2, contents, early life and education edit, iandola grew up in, pearl City, Illinois, and he later attended high school at the. To solve this problem, we propose Trained Ternary Quantization (TTQ a method that can reduce the precision of weights in neural networks to ternary values. Code pdf SqueezeNet: Smaller CNN model is easier to deploy on mobile devices. "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and .5MB model size." arXiv, 2016. Han's research focuses on energy-efficient deep learning, at the intersection between machine learning and computer architecture.
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