Chiyomi Miyajima
Computer Vision and Pattern Recognition · 2007–2019
A researcher in the Science corpus: 8 papers; trusts 38 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 28 citations into it; #13,555 of 21,575 by trust here, #15,529 by citations
- Artificial Intelligence — 21 citations into it; #23,303 of 35,345 by trust here, #26,682 by citations
- Control and Systems Engineering — 7 citations into it
- Model Architectures — 7 citations into it
- Automotive Engineering — 6 citations into it; #730 of 3,081 by trust here, #1,463 by citations
- Safety, Risk, Reliability and Quality — 5 citations into it
- Transportation — 5 citations into it; #2,015 of 2,062 by trust here, #1,495 by citations
Whom Chiyomi Miyajima trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Douglas A. Reynolds
- David M. Blei
- Kazuya Takeda
- Geoffrey E. Hinton
- Alex Krizhevsky
- Karen Simonyan
- Andrew Y. Ng
- Yoshua Bengio
- Ross B. Girshick
Who trusts Chiyomi Miyajima overall
Papers from Chiyomi Miyajima's perspective
Ordered by how strongly the researchers Chiyomi Miyajima 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)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Microsoft COCO: Common Objects in Context
Their papers
- Risky Action Recognition in Lane Change Video Clips using Deep Spatiotemporal Networks with Segmentation Mask Transfer (2019) — 36 citations
- A Traffic Flow Simulation Framework for Learning Driver Heterogeneity from Naturalistic Driving Data using Autoencoders (2019) — 9 citations
- Integrating Driving Behavior and Traffic Context Through Signal Symbolization for Data Reduction and Risky Lane Change Detection (2018) — 31 citations
- Integrating driving behavior and traffic context through signal symbolization (2016) — 7 citations
- Driving Signature Extraction (2015) — 5 citations
- Traffic trajectory history and drive path generation using GPS data cloud (2015) — 9 citations
- International Large-Scale Vehicle Corpora for Research on Driver Behavior on the Road (2011) — 77 citations
- Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification (2007) — 332 citations