Result for "Deep Learning",188

NTT Communication Science Laboratories Open House 2017

Exhibition Program 5 Stable deep learning for time-series data Preventing gradient explosions in gated

https://www.rd.ntt/cs/event/openhouse/2017/exhibition/5/index_en.html

Statistical Machine Learning | NTT Communication Science Laboratories | NTT R&D Website

in deep learning technology have made it possible to build high precision machine learning models for

https://www.rd.ntt/e/cs/team_project/icl/ls/research_innovative02.html

Dr.Naonori Ueda | NTT R&D Website

preparation) Mulia,I.E.,Ueda,N.,Miyoshi,T.,Iwamoto,T.& Heidarzadeh,M.A novel deep learning approach for

https://www.rd.ntt/e/organization/researcher/fellow/f_003.html

Secure Computation AI | NTT R&D Website

data. Advantages of this technology The world's first technology that enables standard deep learning

https://www.rd.ntt/e/research/SI0014.html

PowerPoint Presentation

 Matrix Factorization  Random Walk  Deep Neural Networks The KDD’17 Tutorials  Learning Representations

https://www.rd.ntt/_assets/pdf/sic/event/2018/1/09_panel_jeffrey.pdf

NTT Communication Science Laboratories Open House 2019

, thanks to recent AI developments especially in deep learning, computers are approaching?and surpassing in

https://www.rd.ntt/cs/event/openhouse/2019/director/index_en.html

Media Information Laboratory Past news | NTT Communication Science Laboratories | NTT R&D Website

event representation learning for semantic-level generation and editing of avatar motion” has been

https://www.rd.ntt/e/cs/team_project/media/past_news.html

2020_booklet_en.pdf

- Adaptive spotting for efficient object search 20. Deep learning without data aggregation from nodes

https://www.rd.ntt/cs/event/openhouse/2020/download/2020_booklet_en.pdf

NTT Communication Science Laboratories Open House 2015 Program

- Advances in distant speech recognition by deep learning - Measurement of fluorescence by 9-eye camera

https://www.rd.ntt/cs/event/openhouse/2015/program_en.html

poster.pdf

がります。 0005 Trajectory analysis and prediction using deep learning 1.セグメント分割 2.特徴抽出 3.移動手段判定移動手段推定技術移動軌跡* 時刻

https://www.rd.ntt/cs/event/openhouse/2016/exhibition/5/poster.pdf

スライド 1

on Human Computation and Crowdsourcing （HCOMP2019）, 2019. Deep learning requires much labeled data

https://www.rd.ntt/cs/event/openhouse/2020/download/a_01_en.pdf

Recognition Research Group | NTT Communication Science Laboratories | NTT R&D Website

, Brian Kenji Iwana, and Seiichi Uchida, "Attention to warp: Deep metric learning for multivariate time

https://www.rd.ntt/e/cs/team_project/media/recognition/

F14_leaf_e.pdf

on deep learning using space information collected in the verification environment We confirmed and

https://www.rd.ntt/forum/2023/doc/F14_leaf_e.pdf

NTT Communication Science Laboratories Open House 2014 Defeat reverberation: enemy of speech recognition - Advanced speech enhancement and recognition -

reduction and deep learning-based automatic speech recognition. Our proposed system greatly improves

https://www.rd.ntt/cs/event/openhouse/2014/exhibition/20/index_en.html

Wataru Matsuda | NTT Social Informatics Laboratories | NTT R&D Website

by Monitoring DLL Using Deep Learning, Journal of Information Processing 28, 1052-1064 W Matsuda, M

https://www.rd.ntt/e/sil/overview/evangelist/wataru_matsuda.html

NTT コミュニケーション科学基礎研究所 オープンハウス2020

. Harada, G. Zhang, B. Kleijn, “Edge-consensus learning: deep learning on P2P networks with nonhomogeneous

https://www.rd.ntt/cs/event/openhouse/2020/exhibition20/

Recruit | NTT Software Innovation Center | NTT R&D Website

technologies, machine learning and deep learning algorithm, processing platform technologies for big data

https://www.rd.ntt/e/sic/recruit/

poster_en_17.pdf

, called the composite Line Spectral Pair (LSP) representation, and a deep learning-based approach using

https://www.rd.ntt/cs/event/openhouse/2017/exhibition/17/poster_en_17.pdf

NTT Communication Science Laboratories Open House 2020

” such as “media processing” and “data analysis and machine learning” and science for “obtaining a deep

https://www.rd.ntt/cs/event/openhouse/2020/director/index_en.html

Microsoft PowerPoint - C_パネル一覧0501.pptx

にはユーザのあらゆる要望に応えられるメディア生成技術の確立を目指しています。 16 Deep learning opens the way to innovative media generation 金子

https://www.rd.ntt/cs/event/openhouse/2017/exhibition/16/poster16.pdf