LeapMind Inc

31 Seguidores

LeapMind株式会社公式アカウント　　　　　 -　　　　　　　　　　　　　　　　　　　　　　　 [We make Deep Learning technology practical] At LeapMind Inc. we work on making Deep Learning technology easy to use by building a specialized platform. Then, Deep Learning can be utilized in the real world to advance the world one step ahead. We develop technology for computation compression and distributed intelligence to run in a small computing environment. It enables us to apply this technology to IoT devices and robots. Therefore we can see a world where everything is connected. Instead of "research for research", our philosophy is "research for practical use".

deep learning fpga machine learning ai edls2019 ディープラーニング deeplearning leapmind microsoft 飛躍ディエンプラ jal エッジai インテル edgeedge iot azure マイクロソフト jaxa quantization web development アイットビジネス共創ラボ

Ver mais

Atividades
Sobre

LeapMind Inc

Apresentações

JUIZ DLK 組込み向けDeep Learningコンパイラ

Pitch v2.2

2018年1月19日開催　IoTビジネス共創ラボ第6回勉強会

An Introduction of DNN Compression Technology and Hardware Acceleration on FPGA

20180613 [TensorFlow分散学習] Horovodによる分散学習の実装方法と解説

20180831 [DeLTA TECH] DeLTA-FamilyによるIndustry4.1

20180831 [DeLTA TECH] DeLTA-Liteを支える技術（システム構成編）

20180831 [DeLTA TECH] 新・深層の世紀〜第3集ディープラーニング・時代はAIを求めた〜

20180831 [DeLTA TECH] 深く青い脂

20190227［EDLS］進化するAI on Edge 〜 CloudとEdgeの最適な関係

E20190227［EDLS］インテル®︎FPGAによるエッジAI

20190227［EDLS］JAL's INNOVATION エアラインのAI活用

エッジ向けDeepLearningプロジェクトで必要なこと

[Icml2019] parameter efficient training of deep convolutional neural networks by dynamic sparse reparameterization

[Icml2019]LIT: Learned Intermediate Representation Training for Model Compression

[Icml2019] mix hop higher-order graph convolutional architectures via sparsified neighborhood mixing

Survey on optical flow estimation with DL

Final presentation optical flow estimation with DL