JP2018518740A5 - - Google Patents

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Publication number
JP2018518740A5
JP2018518740A5 JP2017556147A JP2017556147A JP2018518740A5 JP 2018518740 A5 JP2018518740 A5 JP 2018518740A5 JP 2017556147 A JP2017556147 A JP 2017556147A JP 2017556147 A JP2017556147 A JP 2017556147A JP 2018518740 A5 JP2018518740 A5 JP 2018518740A5
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JP
Japan
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input data
bias
neural network
artificial neural
present
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JP2017556147A
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English (en)
Japanese (ja)
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JP2018518740A (ja
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Priority claimed from US14/848,288 external-priority patent/US10325202B2/en
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Publication of JP2018518740A publication Critical patent/JP2018518740A/ja
Publication of JP2018518740A5 publication Critical patent/JP2018518740A5/ja
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JP2017556147A 2015-04-28 2016-03-11 バイアス項を介して深層ニューラルネットワーク中にトップダウン情報を組み込むこと Pending JP2018518740A (ja)

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US201562154097P 2015-04-28 2015-04-28
US62/154,097 2015-04-28
US14/848,288 US10325202B2 (en) 2015-04-28 2015-09-08 Incorporating top-down information in deep neural networks via the bias term
US14/848,288 2015-09-08
PCT/US2016/022158 WO2016175925A1 (en) 2015-04-28 2016-03-11 Incorporating top-down information in deep neural networks via the bias term

Publications (2)

Publication Number Publication Date
JP2018518740A JP2018518740A (ja) 2018-07-12
JP2018518740A5 true JP2018518740A5 (cg-RX-API-DMAC7.html) 2019-04-04

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JP2017556147A Pending JP2018518740A (ja) 2015-04-28 2016-03-11 バイアス項を介して深層ニューラルネットワーク中にトップダウン情報を組み込むこと

Country Status (8)

Country Link
US (1) US10325202B2 (cg-RX-API-DMAC7.html)
EP (1) EP3289527A1 (cg-RX-API-DMAC7.html)
JP (1) JP2018518740A (cg-RX-API-DMAC7.html)
KR (1) KR20170140228A (cg-RX-API-DMAC7.html)
CN (1) CN107533665A (cg-RX-API-DMAC7.html)
AU (1) AU2016256315A1 (cg-RX-API-DMAC7.html)
BR (1) BR112017022983A2 (cg-RX-API-DMAC7.html)
WO (1) WO2016175925A1 (cg-RX-API-DMAC7.html)

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US11842280B2 (en) 2017-05-05 2023-12-12 Nvidia Corporation Loss-scaling for deep neural network training with reduced precision
US11651230B2 (en) 2017-06-02 2023-05-16 Nokia Technologies Oy Artificial neural network
US10108538B1 (en) * 2017-07-31 2018-10-23 Google Llc Accessing prologue and epilogue data
CN111656367A (zh) 2017-12-04 2020-09-11 优创半导体科技有限公司 神经网络加速器的系统和体系结构
KR102153791B1 (ko) * 2017-12-20 2020-09-08 연세대학교 산학협력단 인공 신경망을 위한 디지털 뉴런, 인공 뉴런 및 이를 포함하는 추론 엔진
US11531930B2 (en) * 2018-03-12 2022-12-20 Royal Bank Of Canada System and method for monitoring machine learning models
CN108977897B (zh) * 2018-06-07 2021-11-19 浙江天悟智能技术有限公司 基于局部内在可塑性回声状态网络的熔纺工艺控制方法
US20210350236A1 (en) * 2018-09-28 2021-11-11 National Technology & Engineering Solutions Of Sandia, Llc Neural network robustness via binary activation
KR102184655B1 (ko) * 2018-10-29 2020-11-30 에스케이텔레콤 주식회사 비대칭 tanh 활성 함수를 이용한 예측 성능의 개선
US11481667B2 (en) * 2019-01-24 2022-10-25 International Business Machines Corporation Classifier confidence as a means for identifying data drift
US20200242771A1 (en) * 2019-01-25 2020-07-30 Nvidia Corporation Semantic image synthesis for generating substantially photorealistic images using neural networks
DE102019217444A1 (de) * 2019-11-12 2021-05-12 Robert Bosch Gmbh Verfahren und Vorrichtung zur Klassifizierung digitaler Bilddaten
US10929748B1 (en) * 2019-11-26 2021-02-23 Mythic, Inc. Systems and methods for implementing operational transformations for restricted computations of a mixed-signal integrated circuit
US12154032B2 (en) * 2020-02-04 2024-11-26 Dsp Group Ltd. Post-training control of the bias of neural networks
KR20210158697A (ko) * 2020-06-24 2021-12-31 삼성전자주식회사 뉴로모픽 장치 및 뉴로모픽 장치를 이용하여 뉴럴 네트워크를 구현하는 방법
US12216740B2 (en) 2021-01-08 2025-02-04 Bank Of America Corporation Data source evaluation platform for improved generation of supervised learning models
CN113473580B (zh) * 2021-05-14 2024-04-26 南京信息工程大学滨江学院 异构网络中基于深度学习的用户关联联合功率分配方法

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