Danijel Skocaj

Computer Vision and Pattern Recognition · 2012–2021

A researcher in the Science corpus: 6 papers; trusts 506 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 85 citations into it; #10,330 of 21,575 by trust here, #14,151 by citations
• Artificial Intelligence — 63 citations into it; #16,184 of 35,345 by trust here, #21,878 by citations
• Media Technology — 16 citations into it
• Industrial and Manufacturing Engineering — 13 citations into it
• Biophysics — 12 citations into it
• Model Architectures — 9 citations into it
• Civil and Structural Engineering — 7 citations into it
• Radiology, Nuclear Medicine and Imaging — 7 citations into it

Whom Danijel Skocaj trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Alex Krizhevsky
4. Karen Simonyan
5. Geoffrey E. Hinton
6. Shaoqing Ren
7. Yann LeCun
8. Andrew Zisserman
9. Tsung-Yi Lin
10. Yoshua Bengio

Who trusts Danijel Skocaj overall

1. Guoyang Xie
2. Tran Dinh Tien
3. Hanqiu Deng

Papers from Danijel Skocaj's perspective

Ordered by how strongly the researchers Danijel Skocaj 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. ImageNet Large Scale Visual Recognition Challenge
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Going deeper with convolutions

Their papers

• DRÆM – A discriminatively trained reconstruction embedding for surface anomaly detection (2021) — 1,151 citations
• 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
• Reconstruction by inpainting for visual anomaly detection (2020) — 732 citations
• Deep Learning for Large-Scale Traffic-Sign Detection and Recognition (2019) — 311 citations
• Causal Learning (2012)