Domen Tabernik

Computer Vision and Pattern Recognition · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 380 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 53 citations into it
• Artificial Intelligence — 22 citations into it
• Media Technology — 9 citations into it
• Model Architectures — 7 citations into it
• Civil and Structural Engineering — 6 citations into it

Whom Domen Tabernik trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Karen Simonyan
4. Ross B. Girshick
5. Geoffrey E. Hinton
6. Shaoqing Ren
7. Yann LeCun
8. Pierre Sermanet
9. Andrew Zisserman
10. Ilya Sutskever

Who trusts Domen Tabernik overall

1. Jakob Bozic

Papers from Domen Tabernik's perspective

Ordered by how strongly the researchers Domen Tabernik 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
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. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Segmentation-based deep-learning approach for surface-defect detection (2019) — 909 citations
• Mixed supervision for surface-defect detection: from weakly to fully supervised learning (2021) — 381 citations
• Deep Learning for Large-Scale Traffic-Sign Detection and Recognition (2019) — 311 citations