Mary M. Hayhoe

Computer Vision and Pattern Recognition · 1995–2020

A researcher in the Science corpus: 12 papers; trusts 74 researchers and is trusted by 45 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 104 citations into it; #10,970 of 21,575 by trust here, #7,852 by citations
• Cognitive Neuroscience — 99 citations into it; #437 of 10,852 by trust here, #977 by citations
• Artificial Intelligence — 33 citations into it
• Human-Computer Interaction — 33 citations into it; #103 of 2,253 by trust here, #108 by citations
• Reinforcement Learning — 29 citations into it
• Cognitive Science & Psychology — 16 citations into it; #188 of 582 by trust here, #241 by citations
• Social Psychology — 16 citations into it
• Sensory Systems — 15 citations into it

Whom Mary M. Hayhoe trusts overall

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

1. Laurent Itti
2. M. Land
3. J. Henderson
4. Christof Koch
5. Wolfram Schultz
6. Roland S. Johansson
7. Marvin M. Chun
8. P. R. Montague
9. Okihide Hikosaka
10. Peter McLeod

Who trusts Mary M. Hayhoe overall

1. M. Land
2. Keith Rayner
3. Matthew Botvinick
4. Marianne Gullberg
5. Ali Borji
6. B. Tatler
7. Mariann R Weierich
8. A. Hollingworth
9. William H. Warren Jr.
10. Robert Eamon Briscoe

Papers from Mary M. Hayhoe's perspective

Ordered by how strongly the researchers Mary M. Hayhoe 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. ImageNet: A large-scale hierarchical image database
4. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Et al
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Task and context determine where you look. (2016) — 424 citations
• AGIL: Learning Attention from Human for Visuomotor Tasks (2018) — 85 citations
• Eye movements in natural behavior. (2005) — 1,392 citations
• Eye guidance in natural vision: Reinterpreting salience (2011) — 776 citations
• Human Gaze Assisted Artificial Intelligence: A Review (2020) — 82 citations
• Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset (2019) — 82 citations
• Visual Attention Guided Deep Imitation Learning (2017)
• Adaptive Gaze Control in Natural Environments (2009) — 172 citations
• Visual memory and motor planning in a natural task. (2003) — 610 citations
• In what ways do eye movements contribute to everyday activities? (2001) — 981 citations
• Vision Using Routines: A Functional Account of Vision (2000) — 297 citations
• Deictic Codes for the Embodiment of CognitionDana (1995)