Ismaïla Seck

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 5 citations into it
• Generative Models — 5 citations into it

Whom Ismaïla Seck trusts overall

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

1. Mehdi Mirza
2. Alec Radford
3. Joaquin Quionero-Candela
4. Mario Lucic
5. Simon Osindero
6. Geoffrey E. Hinton
7. Luke Metz
8. Masashi Sugiyama
9. Karol Kurach

Papers from Ismaïla Seck's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Learning Multiple Layers of Features from Tiny Images
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Baselines and a datasheet for the Cerema AWP dataset (2018) — 12 citations