Stephen Marshall

Computer Vision and Pattern Recognition · with Ren · 2016–2019

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 17 citations into it

Whom Stephen Marshall trusts overall

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

1. Alex Krizhevsky
2. Yann LeCun
3. Richard G. Brereton
4. Dilpreet Kaur

Who trusts Stephen Marshall overall

1. Enes Ayan

Papers from Stephen Marshall's perspective

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

1. ImageNet: A large-scale hierarchical image database
2. Learning Multiple Layers of Features from Tiny Images
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Going deeper with convolutions
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Distinctive Image Features from Scale-Invariant Keypoints
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Breast cancer detection using deep convolutional neural networks and support vector machines (2019) — 420 citations
• Novel segmented stacked autoencoder for effective dimensionality reduction and feature extraction in hyperspectral imaging (2016) — 363 citations