Andrés Camero

Artificial Intelligence · 2018–2022

A researcher in the Science corpus: 9 papers; trusts 97 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 80 citations into it; #19,489 of 35,345 by trust here, #24,417 by citations
• Computer Vision and Pattern Recognition — 47 citations into it; #12,703 of 21,575 by trust here, #19,310 by citations
• Model Architectures — 32 citations into it
• Optimization & Training — 23 citations into it
• Electrical and Electronic Engineering — 22 citations into it
• Management Science and Operations Research — 20 citations into it
• Neural Architecture Search & AutoML — 16 citations into it
• Building and Construction — 8 citations into it; #972 of 2,909 by trust here, #2,071 by citations

Whom Andrés Camero trusts overall

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

1. Yoshua Bengio
2. Diederik P. Kingma
3. Thomas Bäck
4. Jamal Toutouh
5. Risto Miikkulainen
6. Geoffrey E. Hinton
7. Enrique Alba
8. Yann LeCun
9. A. Elsaid
10. Jimmy Ba

Who trusts Andrés Camero overall

1. Enrique Alba
2. Jamal Toutouh
3. Javier Ferrer
4. Yuqiao Liu
5. Thomas Bäck
6. Yanan Sun
7. Bing Xue

Papers from Andrés Camero's perspective

Ordered by how strongly the researchers Andrés Camero 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation (2022) — 141 citations
• Bayesian Neural Architecture Search using A Training-Free Performance Metric (2020) — 28 citations
• A Specialized Evolutionary Strategy Using Mean Absolute Error Random Sampling to Design Recurrent Neural Networks (2019) — 16 citations
• Waste generation prediction under uncertainty in smart cities through deep neuroevolution (2019) — 14 citations
• Random error sampling-based recurrent neural network architecture optimization (2019) — 25 citations
• Smart City and information technology: A review (2019) — 360 citations
• Evolutionary Deep Learning for Car Park Occupancy Prediction in Smart Cities (2018) — 102 citations
• Low-Cost Recurrent Neural Network Expected Performance Evaluation (2018) — 20 citations
• DLOPT: Deep Learning Optimization Library (2018) — 9 citations