Mete Ozay
Computer Vision and Pattern Recognition · with Okatani · 2018
A researcher in the Science corpus: 3 papers; trusts 671 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 102 citations into it; #12,425 of 21,575 by trust here, #13,269 by citations
- Artificial Intelligence — 40 citations into it
- Media Technology — 22 citations into it; #1,838 of 3,621 by trust here, #1,696 by citations
- Model Architectures — 20 citations into it
- Generative Models — 19 citations into it
- Optimization & Training — 9 citations into it
- Aerospace Engineering — 8 citations into it
- Neural Architecture Search & AutoML — 7 citations into it
Whom Mete Ozay trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Yann LeCun
- Kaiming He
- Diederik P. Kingma
- Yoshua Bengio
- Ilya Sutskever
- Ross B. Girshick
- Karen Simonyan
- Jia Deng
Who trusts Mete Ozay overall
- Wei Yin
- Masanori Suganuma
- Yi-Wei Chen
- Shariq Farooq Bhat
- Haokui Zhang
- Yunpeng Chen
- Dmytro Mishkin
- Yuqiao Liu
- Dehua Song
Papers from Mete Ozay's perspective
Ordered by how strongly the researchers Mete Ozay 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Revisiting Single Image Depth Estimation: Toward Higher Resolution Maps With Accurate Object Boundaries (2018) — 425 citations
- Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search (2018) — 92 citations
- Deep Structured Energy-Based Image Inpainting (2018) — 16 citations