Logan Ford

Signal Processing · 2019

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Signal Processing — 13 citations into it; #6,553 of 7,572 by trust here, #5,340 by citations
• Computer Vision and Pattern Recognition — 8 citations into it; #18,943 of 21,575 by trust here, #17,258 by citations
• Artificial Intelligence — 6 citations into it; #31,005 of 35,345 by trust here, #26,682 by citations

Whom Logan Ford trusts overall

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

1. Karol J. Piczak
2. Diederik P. Kingma
3. Kaiming He
4. Justin Salamon
5. Jimmy Ba
6. Changsong Yu
7. Annamaria Mesaros
8. Aren Jansen
9. Emre Çakir
10. X. Zhang

Who trusts Logan Ford overall

1. Haytham M. Fayek
2. Shawn Hershey
3. Qiuqiang Kong
4. Andrew Jaegle
5. Anurag Kumar
6. Eduardo Fonseca
7. D. Ellis

Papers from Logan Ford's perspective

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

Their papers

• A Deep Residual Network for Large-Scale Acoustic Scene Analysis (2019) — 52 citations