Andrés Ferraro
Computer Vision and Pattern Recognition · 2017–2021
A researcher in the Science corpus: 3 papers; trusts 62 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 29 citations into it; #19,625 of 21,575 by trust here, #20,756 by citations
- Signal Processing — 28 citations into it; #6,855 of 7,572 by trust here, #7,112 by citations
- Artificial Intelligence — 21 citations into it
- Evaluation & Benchmarks — 13 citations into it; #2,243 of 3,147 by trust here, #2,040 by citations
- Speech & Audio — 7 citations into it; #767 of 1,076 by trust here, #628 by citations
- Model Architectures — 5 citations into it
- Optimization & Training — 5 citations into it
Whom Andrés Ferraro trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Eduardo Fonseca
- Diederik P. Kingma
- Karen Simonyan
- Kaiming He
- Sergey Ioffe
- Jimmy Ba
- Geoffrey E. Hinton
- Richard Zhang
- Alex Krizhevsky
- Christian Szegedy
Who trusts Andrés Ferraro overall
Papers from Andrés Ferraro's perspective
Ordered by how strongly the researchers Andrés Ferraro trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
Their papers
- Improving Sound Event Classification by Increasing Shift Invariance in Convolutional Neural Networks (2021) — 11 citations
- Evaluation of CNN-based Automatic Music Tagging Models (2020) — 113 citations
- Freesound Datasets: A Platform for the Creation of Open Audio Datasets (2017) — 277 citations