Isabel Sargent

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 56 citations into it
• Media Technology — 51 citations into it
• Atmospheric Science — 20 citations into it
• Ecology — 19 citations into it
• Artificial Intelligence — 16 citations into it

Whom Isabel Sargent trusts overall

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

1. Thomas Blaschke
2. Yushi Chen
3. J. Urgen Schmidhuber
4. Dorin Comaniciu
5. Robert Gilmore Pontius Jr.
6. Joachim Niemeyer
7. Geoffrey E. Hinton
8. Thomas J. Pingel
9. Alex Krizhevsky
10. Yann LeCun

Who trusts Isabel Sargent overall

1. Zhuo Zheng

Papers from Isabel Sargent's perspective

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

1. Going deeper with convolutions
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. ImageNet Large Scale Visual Recognition Challenge
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Deep Learning
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Joint Deep Learning for land cover and land use classification (2019) — 458 citations
• An object-based convolutional neural network (OCNN) for urban land use classification (2018) — 423 citations
• A hybrid MLP-CNN classifier for very fine resolution remotely sensed image classification (2017) — 391 citations