Yoshihiko Nakamura
Control and Systems Engineering · 2000–2015
A researcher in the Science corpus: 9 papers; trusts 62 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Control and Systems Engineering — 35 citations into it; #1,819 of 8,257 by trust here, #1,943 by citations
- Computer Vision and Pattern Recognition — 34 citations into it; #7,623 of 21,575 by trust here, #11,083 by citations
- Artificial Intelligence — 21 citations into it
- Human-Computer Interaction — 12 citations into it
- Computational Mechanics — 10 citations into it
- Social Psychology — 10 citations into it; #2,729 of 15,694 by trust here, #5,648 by citations
- Biomedical Engineering — 9 citations into it; #5,566 of 10,734 by trust here, #7,109 by citations
- Cognitive Neuroscience — 9 citations into it; #6,596 of 10,852 by trust here, #7,860 by citations
Whom Yoshihiko Nakamura trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Sylvain Calinon
- Aude Gemma Billard
- Stefan Schaal
- Lawrence R. Rabiner
- Tetsunari Inamura
- Giacomo Rizzolatti
- Geoffrey E. Hinton
- Steven M. LaValle
- Gabriel Taubin
- Michael I. Jordanzoubin
Who trusts Yoshihiko Nakamura overall
- Sylvain Calinon
- Dana Kulic
- Aude Gemma Billard
- Luiza Mici
- Seyed Mohammad Khansari-Zadeh
- James J. Kuffner Jr.
- Wataru Takano
- Seyed Reza Ahmadzadeh
- Takayuki Osa
- Mrinal Kalakrishnan
Papers from Yoshihiko Nakamura's perspective
Ordered by how strongly the researchers Yoshihiko Nakamura trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- GENERATIVE ADVERSARIAL NETS
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains (2008) — 233 citations
- Real-time humanoid motion generation through ZMP manipulation based on inverted pendulum control (2002) — 514 citations
- Embodied Symbol Emergence Based on Mimesis Theory (2004) — 366 citations
- Dynamics filter - concept and implementation of online motion generator for human figures (2000) — 332 citations
- Humanoid Robot's Autonomous Acquisition of Proto-Symbols through Motion Segmentation (2006) — 93 citations
- Incremental learning of full body motion primitives and their sequencing through human motion observation (2012) — 248 citations
- Spatial adaption of robot trajectories based on laplacian trajectory editing (2015) — 23 citations
- Motion Recognition Employing Multiple Kernel Learning of Fisher Vectors Using Local Skeleton Features (2015) — 16 citations
- Unified Impedance and Admittance Control (2010) — 347 citations