Mikel Canizo

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it
• Control and Systems Engineering — 5 citations into it

Whom Mikel Canizo trusts overall

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

1. Salvador Garcia
2. Alex Krizhevsky
3. Lovekesh Vig
4. Lida Abdi
5. Francisco Javier Ordonez
6. Rahul Dey
7. Alberto Fernández
8. Yuequan Bao
9. Pavel Golik
10. Geoffrey E. Hinton

Who trusts Mikel Canizo overall

1. Benjamin Lindemann
2. Yiyuan Yang
3. Benjamin Maschler

Papers from Mikel Canizo's perspective

Ordered by how strongly the researchers Mikel Canizo 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. Long Short-Term Memory
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Going deeper with convolutions
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Multi-head CNN-RNN for multi-time series anomaly detection: An industrial case study (2019) — 360 citations