A. Gardiner

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 A. Gardiner trusts overall

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

1. Thomas Blaschke
2. J. Urgen Schmidhuber
3. Leo Breiman

Papers from A. Gardiner's perspective

Ordered by how strongly the researchers A. Gardiner 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 Learning
4. Gradient-based learning applied to document recognition
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Long Short-Term Memory
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. ImageNet Large Scale Visual Recognition Challenge
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

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