Marko Ristin

Computer Vision and Pattern Recognition · 2014–2016

A researcher in the Science corpus: 3 papers; trusts 368 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 68 citations into it; #10,769 of 21,575 by trust here, #9,722 by citations
• Artificial Intelligence — 42 citations into it; #17,015 of 35,345 by trust here, #14,181 by citations
• Evaluation & Benchmarks — 13 citations into it
• Media Technology — 6 citations into it
• Meta & Continual Learning — 6 citations into it; #523 of 1,041 by trust here, #559 by citations

Whom Marko Ristin trusts overall

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

1. Andrew Zisserman
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Jeffrey Scott Vitter
5. Jia Deng
6. Florent Perronnin
7. Ilya Sutskever
8. David G. Lowe
9. Li Fei-Fei
10. Kaiming He

Who trusts Marko Ristin overall

1. Ali Ayub
2. Abhijit Bendale
3. Alan R. Wagner
4. Nivedita Mishra
5. Yanming Guo
6. Chuanxing Geng
7. Ethan M. Rudd
8. Federico Pernici
9. Sylvestre-Alvise Rebuffi
10. Ragav Venkatesan

Papers from Marko Ristin's perspective

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

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

Their papers

• Incremental Learning of NCM Forests for Large-Scale Image Classification (2014) — 93 citations
• Incremental Learning of Random Forests for Large-Scale Image Classification (2016) — 148 citations
• From categories to subcategories: Large-scale image classification with partial class label refinement (2015) — 59 citations