arXiv:0706.3639v1 [cs.AI] 25 Jun 2007

arXiv:0706.3639v1 [cs.AI] 25 Jun 2007 Technical Report IDSIA-07-07 A Collection of Definitions of Intelligence Shane Legg IDSIA, Galleria …

  Intelligence, Collection

Deep Residual Learning for Image Recognition - …

Deep Residual Learning for Image Recognition Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun Microsoft Research fkahe, v-xiangz, v-shren, jiansung@microsoft.com

  Image, Learning, Residual, Recognition, Residual learning for image recognition

arXiv:1301.3781v3 [cs.CL] 7 Sep 2013

For all the following models, the training complexity is proportional to O = E T Q; (1) where E is number of the training epochs, T is the number of …

@google.com arXiv:1609.03499v2 [cs.SD] 19 Sep 2016

where 1 <x t <1 and = 255. This non-linear quantization produces a significantly better reconstruction than a simple linear quantization scheme. …

A Tutorial on UAVs for Wireless Networks: …

A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems Mohammad Mozaffari 1, ... to UAVs in wireless communications is the work in …

  Network, Communication, Wireless, Wireless communications, Wireless networks

Adversarial Generative Nets: Neural Network …

Adversarial Generative Nets: Neural Network Attacks on State-of-the-Art Face Recognition Mahmood Sharif, Sruti Bhagavatula, Lujo Bauer Carnegie Mellon University

  Network, Attacks, Nets, Adversarial generative nets, Adversarial, Generative, Neural network, Neural, Neural network attacks

Massive Exploration of Neural Machine Translation ...

Massive Exploration of Neural Machine Translation Architectures Denny Britzy, Anna Goldie, Minh-Thang Luong, Quoc Le fdennybritz,agoldie,thangluong,qvlg@google.com Google Brain

  Architecture, Machine, Exploration, Translation, Neural, Exploration of neural machine translation, Exploration of neural machine translation architectures

Mastering Chess and Shogi by Self-Play with a …

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm David Silver, 1Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, 1Matthew Lai, Arthur Guez, Marc Lanctot,1

Going deeper with convolutions - arXiv

Going deeper with convolutions Christian Szegedy Google Inc. Wei Liu University of North Carolina, Chapel Hill Yangqing Jia Google Inc. Pierre Sermanet

  With, Going, Going deeper with convolutions, Deeper, Convolutions

Andrew G. Howard Menglong Zhu Bo Chen Dmitry ...

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand Marco Andreetto Hartwig Adam

  Applications

Fiber Backhaul - Network Building

As of the end of 2012 only approximately 40% of the United State’s 300,000 cell sites had fiber backhaul, however it is estimated that the penetration is over 90% in urban markets and below 30% in rural markets.5 This is mainly in response to the increased data demand as

  Brief, Backhaul, Fiber backhaul

GPON in Mobile Backhaul Final - TEC

2 In the mobile network, cell site base stations are connected to their network controllers by the mobile backhaul (MBH) network. Traditionally, this is a TDM network optimized for voice

  Mobile, Gpon, Backhaul, Gpon in mobile backhaul

Hart-IP: Large Scale System Integration - Emerson

www.ceasiamag.com • CONTROL ENGINEERING ASIA | 19 e a protocol used for the backhaul network between WirelessHart gateways and the control system …

  System, Large, Scale, Integration, Backhaul, Large scale system integration

FirstNet and LTE Overview - FloridaNet

A Key Asset forfirstNet - Spectrum FirstNet The Spectrum Act (a portion of the Middle Class Tax Relief and Job Creation Act) mandated the FCC hold four types of spectrum license

  Overview, Lte overview

FLASHWAVE 7120 - Fujitsu

3 The unique FLASHWAVE 7120 photonic layer solution combines the reliability and management of traditional optical transport systems with flexibility and cost-efficiency.

  2017, Flashwave, Fujitsu, Flashwave 7120

Infrastructure Deployment and Developing Competition

Infrastructure Deployment and Developing Competition 61 Broadband Networks in the Middle East and North Africa • http://dx.doi.org/10.1596/978-1-4648-0112-9

  Infrastructures, Developing, Competition, Deployment, Infrastructure deployment and developing competition