Daniel Fabbri

Computer Vision and Pattern Recognition · 2015–2017

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 8 citations into it; #13,060 of 21,575 by trust here, #14,151 by citations

Whom Daniel Fabbri trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky

Who trusts Daniel Fabbri overall

1. Arvid Lundervold
2. Parnian Afshar

Papers from Daniel Fabbri's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Dropout: a simple way to prevent neural networks from overfitting
4. A Fast Learning Algorithm for Deep Belief Nets
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. GradientBased Learning Applied to Document Recognition
7. Maxout Networks
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Long Short-Term Memory
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Deep Learning for Brain Tumor Classification (2017) — 329 citations
• Toward Content Based Image Retrieval with Deep Convolutional Neural Networks (2015) — 49 citations