David A. Shamma
Computer Vision and Pattern Recognition · 2009–2016
A researcher in the Science corpus: 8 papers; trusts 380 researchers and is trusted by 1,558 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 171 citations into it; #1,039 of 21,575 by trust here, #713 by citations
- Artificial Intelligence — 89 citations into it
- Natural Language Processing — 54 citations into it
- Evaluation & Benchmarks — 48 citations into it; #644 of 3,147 by trust here, #121 by citations
- Computer Science Applications — 18 citations into it
- Information Retrieval & Search — 9 citations into it; #684 of 1,022 by trust here, #195 by citations
Whom David A. Shamma trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- David G. Lowe
- Jia Deng
- Ilya Sutskever
- Ross B. Girshick
- Kaiming He
- Li Fei-Fei
- Andrew Zisserman
- Yoshua Bengio
Who trusts David A. Shamma overall
- Hassan Saif
- Adam Bermingham
- Justin Johnson
- Ishan Misra
- Abhinav Kumar Gupta
- Anastasia Giahanou
- Li Fei-Fei
- Miriam Fernández
- Ranjay Krishna
- Trevor Darrell
Papers from David A. Shamma's perspective
Ordered by how strongly the researchers David A. Shamma 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
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations (2016) — 6,638 citations
- Image retrieval using scene graphs (2015) — 1,234 citations
- The New Data and New Challenges in Multimedia Research (2015) — 332 citations
- Embracing Error to Enable Rapid Crowdsourcing (2016) — 93 citations
- Faces engage us: photos with faces attract more likes and comments on Instagram (2014) — 452 citations
- YFCC100M (2015) — 995 citations
- Characterizing debate performance via aggregated twitter sentiment (2010) — 534 citations
- Tweet the debates: understanding community annotation of uncollected sources (2009) — 389 citations