Result for "deep neural networks",148

NTT Communication Science Laboratories Open House 2018

Exhibition Program 5 Memory efficient deep learning for mobile devices Quantized neural networks for model

https://www.rd.ntt/cs/event/openhouse/2018/exhibition/5/index_en.html

NTT Communication Science Laboratories Open House 2018

trained layered neural networks Abstract The effectiveness of layered neural networks is widely

https://www.rd.ntt/cs/event/openhouse/2018/exhibition/7/index_en.html

Tomoyasu Horikawa | NTT R&D Website

). Keywords brain decoding, deep neural networks, functional magnetic resonance imaging (fMRI), mental imagery

https://www.rd.ntt/e/organization/researcher/special/s_077.html

スライド 1

effectiveness of layered neural networks is widely acknowledged for a wide range of tasks, including image

https://www.rd.ntt/cs/event/openhouse/2018/exhibition/7/poster_en_7.pdf

スライド 1

スライド 1 Contact References Abstract Copyright (C) 2018 NTT corp. All Rights Reserved. Deep Neural

https://www.rd.ntt/cs/event/openhouse/2018/exhibition/5/poster_en_5.pdf

NTT Communication Science Laboratories Open House 2018 Program

environmental sensing and machine learning Memory efficient deep learning for mobile devices Quantized neural

https://www.rd.ntt/cs/event/openhouse/2018/program_en.html

NTT Communication Science Laboratories Open House 2018

Quantized neural networks for model compression Optics makes machine learning much faster Photonic reservoir

https://www.rd.ntt/cs/event/openhouse/2018/en_simple/index_en.html

NTT Communication Science Laboratories Open House 2016

walking, train ,and car by utilizing deep neural networks (DNNs) that automatically extract movement

https://www.rd.ntt/cs/event/openhouse/2016/exhibition/5/index_en.html

poster_en.pdf

transportation modes such as walking, train ,and car by utilizing deep neural networks (DNNs) that automatically

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

poster_en_20.pdf

., “Context adaptive deep neural networks for fast acoustic model adaptation,” in Proc. ICASSP, 2015 [2

https://www.rd.ntt/cs/event/openhouse/2017/exhibition/20/poster_en_20.pdf

Yasutoshi Ida | NTT R&D Website

Based Preconditioning for Deep Neural Networks", International Joint Conference on Artificial

https://www.rd.ntt/e/organization/researcher/special/s_064.html

Deep Image Generation Based on Optics and Physics | NTT Communication Science Laboratories | NTT R&D Website

are composed of black-box neural networks and do not always generate images that are optically or

https://www.rd.ntt/e/cs/team_project/media/recognition/research_media21.html

Problem Solving Will Not Reduce the Number of Research Themes―It Will Open up New Research Areas | NTT R&D Website

artificial intelligence (AI) started around 2012, since then, neural networks based on deep learning have

https://www.rd.ntt/e/research/JN202203_17523.html

スライド 1

characteristics ・Block online processing 17 Who spoke when & what? How many people were there? - All-neural source

https://www.rd.ntt/cs/event/openhouse/2019/download/17_c_en.pdf

poster_en.pdf

fields by training deep neural networks. Our algorithm adapts learning rate by using directions of past

https://www.rd.ntt/cs/event/openhouse/2016/exhibition/7/poster_en.pdf

Smart Traffic Coordination via Learnable Digital Twins-Future Possibilities of Distributed Deep Learning | NTT R&D Website

decentralized federated learning project aims to train model parameters (e.g., in neural networks) under a

https://www.rd.ntt/e/research/JN202208_19150.html

poster_en18.pdf

Laboratory [1] Y. Kubo, T. Hori, A. Nakamura, “Integrating deep neural networks into structured

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/media6/poster_en18.pdf

C20_パネル一覧0501

, K. Kinoshita, T. Hori, T. Nakatani, “Context adaptive deep neural networks for fast acoustic model

https://www.rd.ntt/cs/event/openhouse/2017/exhibition/20/poster20.pdf

スライド 1

, “Modular representation of layered neural networks,” Neural Networks, Vol. 97, pp. 62-73, 2018. [2] 渡邊千紘，平松

https://www.rd.ntt/cs/event/openhouse/2018/exhibition/7/poster7.pdf

poster_en_16.pdf

, “Adaptive visual feedback generation for facial expression improvement with multi-task deep neural networks

https://www.rd.ntt/cs/event/openhouse/2017/exhibition/16/poster_en_16.pdf

poster18.pdf

, A. Nakamura, “Integrating deep neural networks into structured classification approach based on

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/media6/poster18.pdf

NTT Communication Science Laboratories Open House 2013 Transcribing every word whoever speaks - Speech recognizers robust to casual speech variations -

the full-size PDF file. Reference Y. Kubo, T. Hori, A. Nakamura, “Integrating deep neural networks

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/media6/index_en.html

Toshiki Shibahara | NTT Social Informatics Laboratories | NTT R&D Website

neural networks and privacy protection with differential privacy. Awards CSS Best Paper Award (2018, 2022

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

NTT Communication Science Laboratories Open House 2019

based on neural networks When children begin to understand hiragana Emergent literacy development in

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

poster_en_5.pdf

method to stabilize training of Recurrent Neural Networks (RNNs). The RNN is one of the most successful

https://www.rd.ntt/cs/event/openhouse/2017/exhibition/5/poster_en_5.pdf

NTT Communication Science Laboratories Open House 2020 Exhibition

recovery-command sequences by neural networks Refining spatially aggregated data from cities Multivariate

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

NTT Communication Science Laboratories Open House 2020

resonance (CMR) imaging, by combining it with the deep neural networks-based anatomical segmentation of CMR

https://www.rd.ntt/cs/event/openhouse/2020/exhibition21/index_en.html

井田 安俊 | NTT R&D Website

Learning Rate via Covariance Matrix Based Preconditioning for Deep Neural Networks", International Joint

https://www.rd.ntt/organization/researcher/special/s_064.html

Dr.Naonori Ueda | NTT R&D Website

Chemical Research, 2003-September 2012. Associate Editor, Neural Networks Journal, 2003-2010. General Chair

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

スライド 1

combining it with the deep neural networks-based anatomical segmentation of CMR imaging. Masahiro Nakano

https://www.rd.ntt/cs/event/openhouse/2020/download/c_21_en.pdf

NTT コミュニケーション科学基礎研究所 オープンハウス2013 誰がどのように話しても正確に聞き取ります ～話者や発話スタイルの多様性に頑健な音声認識技術～

deep neural networks into structured classification approach based on weighted finite-state transducers

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/media6/

Secure Computation AI | NTT R&D Website

maintain accuracy in calculations such as reciprocals and square roots, essential for neural networks

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

NTT Communication Science Laboratories Open House 2019

spoke when & what? How many people were there? - All-neural source separation, counting and diarization

https://www.rd.ntt/cs/event/openhouse/2019/exhibition17/index_en.html

Microsoft PowerPoint - C_パネル一覧0501.pptx

facial expression improvement with multi-task deep neural networks,” in Proc. The 24th ACM International

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

Visual Mechanisms for Perceiving Materials | NTT Communication Science Laboratories | NTT R&D Website

be computed by neural networks in the retina or in the low-level visual cortex. Changing Materials by

https://www.rd.ntt/e/cs/team_project/human/representation/research_human01.html

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

Visual Feedback Generation for Facial Expression Improvement with Multi-task Deep Neural Networks", The

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

Signal Processing Research Group | NTT Communication Science Laboratories | NTT R&D Website

Of Neural- And Clustering-Based Diarization Through Deep Unfolding Of Infinite Gaussian Mixture Model

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

Science and Technology Are the Collective Wisdom of Our Predecessors. It Is Our Mission-the Researchers of Today-to Make Them Even Better | NTT R&D Website

deep learning and neural networks, it is important to repeat the process of verifying a hypothesis

https://www.rd.ntt/e/research/JN202305_21819.html

NTT Communication Science Laboratories Open House 2017

recurrent units Abstract We propose a method to stabilize training of Recurrent Neural Networks (RNNs). The

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

スライド 1

Face-to-voice conversion and voice-to-face conversion - Crossmodal voice conversion with deep

https://www.rd.ntt/cs/event/openhouse/2019/download/19_c_en.pdf

Unsupervised Learning of 3D Representations from 2D images | NTT Communication Science Laboratories | NTT R&D Website

overcome this limitation, we developed a deep generative model that uses a camera aperture rendering

https://www.rd.ntt/e/cs/team_project/media/recognition/research_media15.html

poster_en_13.pdf

networks / Deep learning [low memory requirement] able to provide WEVs 10 to 100 times smaller than those

https://www.rd.ntt/cs/event/openhouse/2017/exhibition/13/poster_en_13.pdf

上田 修功 | NTT R&D Website

. Associate Editor, Neural Networks Journal, 2003-2010. 電子情報通信学会 情報論的学習理論時限研究専門委員会, 専門委員長, 2003-2004年. 情報論的学習

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

信号処理研究グループ｜NTTコミュニケーション科学基礎研究所｜NTT R&D Website

Of Neural- And Clustering-Based Diarization Through Deep Unfolding Of Infinite Gaussian Mixture Model

https://www.rd.ntt/cs/team_project/media/signal/

Communication with Desired Voice | NTT R&D Website

input speech and target speech. 2. Research on speech × deep generative model A typical voice-conversion

https://www.rd.ntt/e/research/JN202009_6715.html

Photonic Implementation of Reservoir Computing | NTT R&D Website

artificial neural networks (ANNs). Their computation is based on a huge amount of matrix operations and

https://www.rd.ntt/e/research/JN202206_18595.html

Optical Circuit Technologies for Next-generation Computing Using Light | NTT R&D Website

the research introduced in this article, research on neural networks using optical circuits has been

https://www.rd.ntt/e/research/JN202206_18579.html

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

Neural Networks” has been accepted to The Journal of the Acoustical Society of America Express Letters

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

メディア認識研究グループ｜NTTコミュニケーション科学基礎研究所｜NTT R&D Website

N. Harada, "Phase reconstruction based on recurrent phase unwrapping with deep neural networks," in

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

Report on the NTT R&D Forum — Road to IOWN 2022｜NTT R&D Website

. The AI boom is supported by deep learning technology. Its many layers of neural networks learn from a

https://www.rd.ntt/e/forum/2022/keynote_2.html

H1-H4

for facial expression improvement with multi-task deep neural networks,” in Proc. 24th ACM

https://www.rd.ntt/cs/event/openhouse/2017/talk/research2/talk_kaneko.pdf

Developing AI that Pays Attention to Who You Want to Listen to: Deep-learning-based Selective Hearing with SpeakerBeam｜NTT R&D Website

Developing AI that Pays Attention to Who You Want to Listen to: Deep-learning-based Selective

https://www.rd.ntt/e/research/JN202107_14481.html

Speech information processing | NTT R&D Website

Neural Voice Activity Detection Using Auxiliary Networks for Phoneme Recognition, Speech Enhancement and

https://www.rd.ntt/e/hil/category/voice/

同調圧力に鈍感であれ。自由な時間は成功要因の1つである｜NTT R&D Website

: Insights from deep neural networks，”PLoS Computational Biology, Vol, 16, No. 8, e1008018-29，2020. (5)http

https://www.rd.ntt/research/JN202103_11095.html

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

-Supervised Learning” was accepted to IEEE International Joint Conference on Neural Networks (IJCNN). https

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

2020_booklet_en.pdf

. Presenting a quick solution to system failures - Generating recovery-command sequences by neural networks 03

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

R&D on Security Contributing to Creation of New Value | NTT R&D Website

computation technology enables model training with a deep neural network while training data are kept secret

https://www.rd.ntt/e/research/JN20200210_h.html

Learning 3D Information from 2D Images Using Aperture Rendering Generative Adversarial Networks toward Developing a Computer that "Understands the 3D World" | NTT R&D Website

learning model," which does not require pre-determined correct answers, and consists of two neural networks

https://www.rd.ntt/e/research/JN202205_18199.html

Be Insensitive to Peer Pressure to Fight a Fierce Battle of Ideas｜NTT R&D Website

of Liquids: Insights from Deep Neural Networks,” PLoS Computational Biology, Vol. 16, No. 8, e1008018

https://www.rd.ntt/e/research/JN202103_11095.html

多様なユースケースに適用可能な音声合成エンジン「Saxe」｜NTT R&D Website

を」「所望の話者の声で」「多様な動作環境で」音声を生成することが求められています。NTTメディアインテリジェンス研究所ではこれらの課題に対し、DNN（Deep Neural Networks）に基づく音声合成

https://www.rd.ntt/research/JN202010_7500.html

メディア情報研究部｜NTTコミュニケーション科学基礎研究所｜NTT R&D Website

IEEE International Joint Conference on Neural Networks (IJCNN) に採録されました。 https://arxiv.org/pdf/2603

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

Optical Device Technology for Next-generation Computing Using Light | NTT R&D Website

optical neural networks [3] and optical quantum information processing [4,5] are beginning to be

https://www.rd.ntt/e/research/JN202206_18551.html

Behavioral technology modeling | NTT R&D Website

Covariates", Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 2023. Takeshi Kurashima

https://www.rd.ntt/e/hil/category/behavior_modeling/

If We Pursue Research Properly and Correctly, We Will Accumulate Knowledge That Will Make a Valuable Contribution to Academia | NTT R&D Website

" question. Among artificial neural networks, deep neural networks (DNNs) have a structure like that of the

https://www.rd.ntt/e/research/JN202211_20065.html

AI競争の差別化要因となる「Deep Learningのコアな研究/技術」｜NTT R&D Website

Preconditioning for Deep Neural Networks”, IJCAI 2017. https://www.ijcai.org/proceedings/2017/0267.pdf 技術その2: AI処理

https://www.rd.ntt/research/AP99-320.html

Nanophotonic Technologies toward Opto-electronic Integrated Accelerators | NTT R&D Website

microwave signals (Fig. 2(b))[4]. At the same time, research on optical neural networks is becoming quite

https://www.rd.ntt/e/research/JN202008_5995.html

talk_yoshioka.pdf

using context-dependent deep neural networks,” in Proc. 12th Annual Conference of the International

https://www.rd.ntt/cs/event/openhouse/2016/talk/research1/talk_yoshioka.pdf

Being Different Is a Compliment. Practice Talking Logically about Future Plans｜NTT R&D Website

research objectively and work on something new. I recently started studying graph neural networks to

https://www.rd.ntt/e/research/JN202104_12388.html

Learning and Intelligent Systems Research Group | NTT Communication Science Laboratories | NTT R&D Website

Aoyama, Yuya Hikima, "Natural Perturbations for Black-box Training of Neural Networks by Zeroth-Order

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

知能創発環境研究グループ｜NTTコミュニケーション科学基礎研究所｜NTT R&D Website

Aoyama, Yuya Hikima, "Natural Perturbations for Black-box Training of Neural Networks by Zeroth-Order

https://www.rd.ntt/cs/team_project/icl/ls/

音声情報処理 | NTT R&D Website

, Hiroshi Sato, Kohei Matsuura, Tomohiro Tanaka, Ryo Masumura, "Scheduled Sampling for Neural Transducer

https://www.rd.ntt/hil/category/voice/

Demonstration of a high performance optical logic gate for ultralow-latency data processing｜NTT Basic Research Laboratories | NTT R&D Website

... Neural network accelerators High efficiency and high speed processors specialized for some deep learning

https://www.rd.ntt/e/brl/latesttopics/2020/03/latest_topics_202003061859.html

Human Information Science Laboratory | NTT Communication Science Laboratories | NTT R&D Website

). Perturbation tolerance of deep neural networks and humans in material recognition. CiNet 5th conference. Osaka

https://www.rd.ntt/e/cs/team_project/human/

メディア情報研究部　過去のニュース｜NTTコミュニケーション科学基礎研究所｜NTT R&D Website

from Optical Projections Using Physics-Informed Neural Networks」がThe Journal of the Acoustical Society

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

2019_booklet_english.pdf

-down RST parsing based on neural networks～ 11 When children begin to understand hiragana ～Emergent

https://www.rd.ntt/cs/event/openhouse/2019/download/2019_booklet_english.pdf

Updates | NTT R&D Website

States Based on Time-bin Qubits 08/22/2025 Using Neural Networks to Enable Computers to Listen to Voices

https://www.rd.ntt/e/update_information/

IOWN PETs | NTT R&D Website

: Secure and Fast Training of Deep Neural Networks with Adaptive Moment Estimation. Proc. Priv. Enhancing

https://www.rd.ntt/sil/project/iown-pec/

NTT R&D Forum 2019 Report｜NTT R&D Website

optical digital logic processing and neural networks that integrate optical switches and the new optical

https://www.rd.ntt/e/forum/2019/

Bayesian Nonparametric Methods for Analyzing Ever-increasing Infinite Data | NTT R&D Website

that deep learning rose to prominence from 2012 on thanks to the third boom in neural networks, I began

https://www.rd.ntt/e/research/JN202405_26190.html

デジタルツインでモビリティ群を賢く制御する ――分散深層学習がもたらす未来の可能性 | NTT R&D Website

． ＊3　GAT: Graph Neural Networksの一種で、ノードのつながりの重要度について適応的に更新しながら状態変数を更新する特徴を持ちます。ただし、交通制御等への応用のために提案された方式

https://www.rd.ntt/research/JN202208_19150.html

光を用いて計算する次世代コンピューティングに向けた光回路技術 | NTT R&D Website

aK203-7, 2018. (5)T. Hashimoto ：“Wavefront matching method as a deep neural network and mutual use of

https://www.rd.ntt/research/JN202206_18579.html

交通ダイナミクスやAIモデルの分散学習技術 | NTT R&D Website

, Guoqiang Zhang, Bastiaan Kleijn, "Edge-consensus Learning: Deep Learning on P2P Networks with

https://www.rd.ntt/iown_tech/post_35.html

New Developments in Communication Science Research in the Generative AI Era--Exploring the Nature of Humans and Information for Co-creating Human-centered Technologies with AI | NTT R&D Website

the development of deep learning, as well as a major breakthrough in natural language processing

https://www.rd.ntt/e/research/JN202409_29257.html

人間情報研究部｜NTTコミュニケーション科学基礎研究所｜NTT R&D Website

指令のタイミングのばらつきを小さくすることが重要であることを示した論文が、Neural Networks誌に掲載されました。 Takagi, A., Ito, S., & Gomi, H. (2026

https://www.rd.ntt/cs/team_project/human/

Data Sharing and Utilization Technologies for Safe and Secure Value-creation Processes｜NTT R&D Website

the input data and neural networks encrypted [3]. We are also working on increasing the speed of

https://www.rd.ntt/e/research/JN202104_12213.html

oh2017_booklet.pdf

feedback generation for facial expression improvement with multi-task deep neural networks,” in Proc. 24th

https://www.rd.ntt/cs/event/openhouse/2017/download/oh2017_booklet.pdf

行動モデリング | NTT R&D Website

, Tomoharu Iwata, "Predicting Opinion Dynamics via Sociologically-Informed Neural Networks", In Proceedings

https://www.rd.ntt/hil/category/behavior_modeling/

R&D History | NTT R&D Website

networks. Developed world's fastest 100 Gbit/s optical communication IC. Developed wireless IP access

https://www.rd.ntt/e/about/chronicle/

感性情報処理 | NTT R&D Website

,“Latent Neural Phase Model for Synchronization Analysis”,International Joint Conference on Neural Networks

https://www.rd.ntt/hil/category/emotion/

Computational Modeling Research Group | NTT Communication Science Laboratories | NTT R&D Website

Ishikawa, Noboru Harada & Yasuhiro Oikawa (2025). SoundSil-DS: Deep Denoising and Segmentation of Sound

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

Reach Out and Touch Someone’s Heart: Exploring the Essence of Communication to Create a Spiritually Rich Society｜NTT R&D Website

(emotionally rich and sensitive) communication to convey deep feelings by touch. The “Mega-Futuristic

https://www.rd.ntt/e/research/JN202107_14463.html

論文｜NTT物性科学基礎研究所｜NTT R&D Website

of chimera states in spiking neural networks based on degenerate optical parametric oscillators

https://www.rd.ntt/brl/result/publications/paper_2023.html

Publications | NTT Basic Research Laboratories | NTT R&D Website

of chimera states in spiking neural networks based on degenerate optical parametric oscillators

https://www.rd.ntt/e/brl/result/publications/paper_2023.html

佐々木 元晴 | NTT R&D Website

wireless networks," AGU Radio Science, Vol. 55, Issue 1, e2019RS006924, Jan. 2020, https://doi.org/10.1029

https://www.rd.ntt/organization/researcher/special/s_069.html

Motoharu Sasaki | NTT R&D Website

wireless networks," AGU Radio Science, Vol. 55, Issue 1, e2019RS006924, Jan. 2020, https://doi.org/10.1029

https://www.rd.ntt/e/organization/researcher/special/s_069.html

0081.pdf

frequency range,” in IEEE Interna- tional Workshop on Neural Networks for Signal Processing (NNSP2002), Sept

https://www.rd.ntt/cs/team_project/icl/signal/iwaenc03/cdrom/data/0081.pdf

I Want to Create a World Like That of Astro Boy, Where People and Computers Share the Same Sound Space and Can Freely Cooperate with Each Other｜NTT R&D Website

technologically, we cannot afford not to study. In the field of neural networks, the speed of computers has

https://www.rd.ntt/e/research/JN202201_16891.html

Looking More, Acting Better｜NTT R&D Website

is still under investigation, but it has been reported that various neural networks, including the

https://www.rd.ntt/e/research/JN202107_14478.html

Demonstration of ultrafast and energy-efficient all-optical switching with graphene and plasmonic waveguides｜NTT Basic Research Laboratories | NTT R&D Website

optical neural networks. In the future, we will increase the performance of the all-optical switch, apply

https://www.rd.ntt/e/brl/latesttopics/2019/11/latest_topics_201911261120.html