Ekim Yurtsever
Computer Vision and Pattern Recognition · 2015–2020
A researcher in the Science corpus: 8 papers; trusts 533 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 192 citations into it
- Automotive Engineering — 119 citations into it; #1,341 of 3,081 by trust here, #1,294 by citations
- Aerospace Engineering — 72 citations into it
- Artificial Intelligence — 61 citations into it; #26,505 of 35,345 by trust here, #25,809 by citations
- Control and Systems Engineering — 44 citations into it
- Environmental Engineering — 27 citations into it
- Safety, Risk, Reliability and Quality — 21 citations into it
- Evaluation & Benchmarks — 18 citations into it
Whom Ekim Yurtsever trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Alex Krizhevsky
- Geoffrey E. Hinton
- Ross B. Girshick
- Karen Simonyan
- Andrew Zisserman
- Yoshua Bengio
- Yann LeCun
- Diederik P. Kingma
- Ilya Sutskever
Who trusts Ekim Yurtsever overall
- Jacob Lambert
- Alexander Carballo
- Kazuya Takeda
- Jianyu Chen
- Chiyomi Miyajima
- S. Lo Piano
- Shengbo Eben Li
Papers from Ekim Yurtsever's perspective
Ordered by how strongly the researchers Ekim Yurtsever 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)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- A Survey of Autonomous Driving: Common Practices and Emerging Technologies (2019) — 1,858 citations
- Integrating Deep Reinforcement Learning with Model-based Path Planners for Automated Driving (2020) — 25 citations
- 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