Rima Arnaout

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 3 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 8 citations into it

Whom Rima Arnaout trusts

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

1. Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)
2. L. V. D. van der Maaten (in Computer Vision and Pattern Recognition)

Papers from Rima Arnaout's perspective

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

1. Visualizing Data using t-SNE
2. Machine-Learning Algorithms to Automate Morphological and Functional Assessments in 2D Echocardiography.
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Learning Multiple Layers of Features from Tiny Images
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Attention is All you Need (Neural Information Processing Systems)
8. Gradient-based learning applied to document recognition
9. Long Short-Term Memory
10. Distinctive Image Features from Scale-Invariant Keypoints

Their papers

• Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist (2020) — 485 citations
• Fast and accurate view classification of echocardiograms using deep learning (2018) — 503 citations
• Fast and accurate classification of echocardiograms using deep learning (2017) — 24 citations