Erkut Erdem

Computer Vision and Pattern Recognition · 2013–2023

A researcher in the Science corpus: 10 papers; trusts 912 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 280 citations into it; #5,650 of 21,575 by trust here, #4,137 by citations
• Artificial Intelligence — 117 citations into it; #18,045 of 35,345 by trust here, #13,163 by citations
• Multimodal Learning — 78 citations into it; #1,028 of 1,211 by trust here, #685 by citations
• Natural Language Processing — 78 citations into it; #5,041 of 5,688 by trust here, #4,112 by citations
• Generative Models — 64 citations into it; #1,526 of 1,956 by trust here, #1,287 by citations
• Evaluation & Benchmarks — 57 citations into it; #2,033 of 3,147 by trust here, #544 by citations
• Cognitive Neuroscience — 12 citations into it; #3,069 of 10,852 by trust here, #7,860 by citations
• Media Technology — 12 citations into it

Whom Erkut Erdem trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Antonio Torralba
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Kaiming He
6. Yoshua Bengio
7. Yann LeCun
8. Ilya Sutskever
9. Karen Simonyan
10. Ross B. Girshick

Who trusts Erkut Erdem overall

1. Ali Borji
2. E. Vig
3. Xun Huang
4. Ming-Ming Cheng
5. Michael Dorr
6. Chengyao Shen
7. Huaizu Jiang
8. Qi Zhao
9. Eren Golge
10. Li Luo

Papers from Erkut Erdem's perspective

Ordered by how strongly the researchers Erkut Erdem trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Learning to Generate Images of Outdoor Scenes from Attributes and Semantic Layouts (2016) — 192 citations
• Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures (2016) — 393 citations
• Manipulating Attributes of Natural Scenes via Hallucination (2018) — 24 citations
• Re-evaluating Automatic Metrics for Image Captioning (2016) — 194 citations
• RecipeQA: A Challenge Dataset for Multimodal Comprehension of Cooking Recipes (2018) — 196 citations
• Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures (Extended Abstract) (2017) — 25 citations
• Visual saliency estimation by nonlinearly integrating features using region covariances. (2013) — 416 citations
• Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2023) — 266 citations
• Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) — 2,561 citations
• Image Synthesis in Multi-Contrast MRI With Conditional Generative Adversarial Networks (2018) — 581 citations