Result for "Deep Learning",188

poster_en.pdf

【Reference】【Co nt ac t】 Abstract Fast and Accurate Deep Learning Yasutoshi Ida Software Innovation

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

High-speed optical interconnect for AI : Distributed deep learning accelerator | NTT Device Technology Laboratories | NTT R&D Website

High-speed optical interconnect for AI : Distributed deep learning accelerator | NTT Device

https://www.rd.ntt/e/dtl/technology/pe_product-optical-interconnect.html

NTT Communication Science Laboratories Open House 2016

Fast and accurate deep learning - Efficient learning utilizing directions of past gradients - Abstract

https://www.rd.ntt/cs/event/openhouse/2016/exhibition/7/index_en.html

Sekitoshi Kanai | NTT Software Innovation Center | NTT R&D Website

Project Researcher (As of November 2018) Making the current deep learning with AI faster, easier and safer

https://www.rd.ntt/e/sic/team_researchers/researcher/249.html

スライド 1

Improving the accuracy of deep learning - Larger capacity output function for deep learning - Deep learning

https://www.rd.ntt/cs/event/openhouse/2019/download/04_a_en.pdf

NTT Communication Science Laboratories Open House 2019

Improving the accuracy of deep learning - Larger capacity output function for deep learning - Abstract Deep

https://www.rd.ntt/cs/event/openhouse/2019/exhibition4/index_en.html

スライド 1

for efficient object search We propose Adaptive Spotting, a deep reinforcement learning approach to

https://www.rd.ntt/cs/event/openhouse/2020/download/c_19_en.pdf

Network-AI技術 – 主要な外部発表

. Matsuo and K. Watanabe, "Fault Detection of ICT systems with Deep Learning Model for Missing Data, " 2021

https://www.rd.ntt/ns/qos/research/05/presentation.html

スライド 1

from their voices with deep learning model Applications Call center response decision, marketing

https://www.rd.ntt/cs/event/openhouse/2020/download/c_15_en.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

analysis by environmental sensing and machine learning Memory efficient deep learning for mobile devices

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

NTT Communication Science Laboratories Open House 2016

Thursday, June 2th 15:30 - 16:10 Avenues toward super-human speech recognizers - Advances in deep learning

https://www.rd.ntt/cs/event/openhouse/2016/talk/research1/index_en.html

NTT Communication Science Laboratories Open House 2017

Abstract The rapid progress of deep learning is impacting the world we live in. Media generation (e.g

https://www.rd.ntt/cs/event/openhouse/2017/talk/research2/index_en.html

スライド 1

modeling,” under review.[2] T. Ngo, Z. Lu, G. Carneiro,“Combining deep learning and level set for the

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

NTT Communication Science Laboratories Open House 2020

technology and our approaches with the theme "What can be done when the voice is combined with deep learning

https://www.rd.ntt/cs/event/openhouse/2020/research1/index_en.html

スライド 1

Signal Processing Research Group, Media Information Laboratory We propose an AI system (a deep learning

https://www.rd.ntt/cs/event/openhouse/2018/exhibition/17/poster_en_17.pdf

NTT Communication Science Laboratories Open House 2017 Program

) 11:00 - 11:40 Generative personal assistance with audio and visual examples Deep learning opens the

https://www.rd.ntt/cs/event/openhouse/2017/program_en.html

KOBAYASHI, Masahiro

, May 2018. A. Suzuki and M. Kobayashi, "Multi-Agent Deep Reinforcement Learning for Cooperative

https://www.rd.ntt/e/ns/qos/person/m_kobayashi/

田尻 兼悟

, Yasuhiro Ikeda, Yuusuke Nakano, Keishiro Watanabe“Dividing Deep Learning Model for Continuous Anomaly

https://www.rd.ntt/ns/qos/person/tajiri/

Automated Data Analysis "RakuDA" | NTT Software Innovation Center | NTT R&D Website

of distributed data processing platform SE project includes deep learning and machine learning. Our

https://www.rd.ntt/e/sic/team_researchers/team/250.html

NTT Communication Science Laboratories Open House 2020

Spotting, a deep reinforcement learning approach to object search from a scene represented by a 3D point

https://www.rd.ntt/cs/event/openhouse/2020/exhibition19/index_en.html

NTT Communication Science Laboratories Open House 2019

population data Improving the accuracy of deep learning Larger capacity output function for deep learning

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

NTT Communication Science Laboratories Open House 2017

Exhibition Program 16 Generative personal assistance Deep learning opens the way to innovative media

https://www.rd.ntt/cs/event/openhouse/2017/exhibition/16/index_en.html

poster_en_16.pdf

process automatically. To this end, we propose two kinds of learning-based (specifically, deep learning

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

スライド 1

comfort and energy saving ⇒ Maximize conflicting indicators by deep reinforcement learning to calculate

https://www.rd.ntt/cs/event/openhouse/2019/download/02_a_en.pdf

NTT Communication Science Laboratories Open House 2015

Extracting essential information from sounds - Advances in distant speech recognition by deep learning

https://www.rd.ntt/cs/event/openhouse/2015/exhibition/20/index_en.html

Generalized Domain Adaptation | NTT Communication Science Laboratories | NTT R&D Website

is well-known that deep-learning models degrade in performance when there are environmental

https://www.rd.ntt/e/cs/team_project/media/recognition/research_media16.html

NTT Communication Science Laboratories Open House 2020

, “Edge-consensus learning: deep learning on P2P networks with nonhomogeneous data,” submitted to KDD 2020

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

スライド 1

deep learning explains the tuning in presence of reverberation  The frequency tuning may be optimal

https://www.rd.ntt/cs/event/openhouse/2018/exhibition/24/poster_en_24.pdf

NTT Communication Science Laboratories Open House 2016 Program

deep learning and signal processing that are making speech recognition leap forward - Takuya Yoshioka

https://www.rd.ntt/cs/event/openhouse/2016/program_en.html

NTT Communication Science Laboratories Open House 2016

How did you get here? Where will you go? - Trajectory analysis and prediction using deep learning

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

Network-AI技術

: Deep Anomaly Surveillance」の技術解説 Technical description about Deep Learning Based Anomaly Detection

https://www.rd.ntt/ns/qos/research/05/

Photonic reservoir computing : Optics makes a machine learning much faster | NTT Device Technology Laboratories | NTT R&D Website

Preprocessing of large-scale video streaming to assist deep learning Related technologies Optical packet

https://www.rd.ntt/e/dtl/technology/pe_product-photonic-reservoir.html

MATSUO, Yoichi

researches on network management. Research Interests Network operation Machine Learning, Deep Learning

https://www.rd.ntt/e/ns/qos/person/matsuo/

NTT Communication Science Laboratories Open House 2018

hypothesis selection Abstract We propose an AI system (a deep learning model) that solves two-choice

https://www.rd.ntt/cs/event/openhouse/2018/exhibition/17/index_en.html

The Front Line of Data Security｜NTT R&D Website

Learning Processing in the Deep Learning of the Standard AI with Encryption As introduced in the first

https://www.rd.ntt/e/security/0002.html

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

. Recent interests include security of machine-learning-based systems, particularly attacks against deep

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

鈴木 晃人

-Agent Deep Reinforcement Learning for Cooperative Computing Offloading and Route Optimization in Multi

https://www.rd.ntt/ns/qos/person/a_suzuki/

HASHIMOTO, Yuka

. Yuka Hashimoto, Masahiro Ikeda, and Hachem Kadri, Deep learning with kernels through RKHM and the

https://www.rd.ntt/e/ns/qos/person/hashimoto/

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

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

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

スライド 1

Computing Technology Project, Software Innovation Center 05 Memory efficient deep learning for mobile

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

E07_leaf_e.pdf

. Summary Our technology can quickly generate efficient routes using AI (deep reinforcement learning) while

https://www.rd.ntt/forum/2023/doc/E07_leaf_e.pdf

Video Library | Communication Traffic, Quality and Operation Research Project | NTT Network Service Systems Laboratories | NTT R&D Website

learning based anomaly detection technology - DeAnoS: Deep Anomaly Surveillance - Predictive routing

https://www.rd.ntt/e/ns/qos/video_library.html

NTT Communication Science Laboratories Open House 2020 Exhibition

spotting for efficient object search Deep learning without data aggregation from nodes Asynchronous

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

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 2020

physical laws for 3D cardiac modeling,” under review. T. Ngo, Z. Lu, G. Carneiro, “Combining deep learning

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

P11_leaf_e.pdf

computing resources without copying for LLM learning Remote computing with APN - Future of tsuzumis' deep

https://www.rd.ntt/forum/2023/doc/P11_leaf_e.pdf

NTT Communication Science Laboratories Open House 2019

Download Contact Home / Program / Exhibition Program Exhibition Program Science of Machine Learning 05

https://www.rd.ntt/cs/event/openhouse/2019/exhibition5/index_en.html

スライド 1

スライド 1 Abstract References Contact オープンハウス 2020 20 Deep learning without data aggregation from

https://www.rd.ntt/cs/event/openhouse/2020/download/c_20_en.pdf

Getting closer to humans with AI and understanding humans with brain science: AI with a deep understanding of people, capable of coexisting with us｜NTT R&D Website

to near and surpass specific human abilities through research into fields such as deep learning

https://www.rd.ntt/e/ai/0003.html