Antitza Dantcheva

Computer Vision and Pattern Recognition · 2016–2018

A researcher in the Science corpus: 2 papers; trusts 184 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 61 citations into it; #12,845 of 21,575 by trust here, #14,478 by citations
• Signal Processing — 14 citations into it; #4,253 of 7,572 by trust here, #4,051 by citations
• Artificial Intelligence — 10 citations into it
• Biomedical Engineering — 5 citations into it
• Cognitive Neuroscience — 5 citations into it

Whom Antitza Dantcheva trusts overall

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

1. Neeraj Kumar
2. Xin Geng
3. Geoffrey E. Hinton
4. Devi Parikh
5. Alex Krizhevsky
6. Christian Szegedy
7. Narayanan Ramanathan
8. Kaiming He
9. Andrew Zisserman
10. Yoshua Bengio

Who trusts Antitza Dantcheva overall

1. Vahid Mirjalili
2. Lishan Qiao
3. Vishal M. Patel
4. Sebastian Raschka
5. Joy Buolamwini
6. Songcan Chen
7. Arun A. Ross
8. Ramalingam Chellappa
9. Kimmo Kärkkäinen
10. Zachary Bessinger

Papers from Antitza Dantcheva's perspective

Ordered by how strongly the researchers Antitza Dantcheva 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. 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

• Mitigating Bias in Gender, Age and Ethnicity Classification: A Multi-task Convolution Neural Network Approach (2018) — 167 citations
• What Else Does Your Biometric Data Reveal? A Survey on Soft Biometrics (2016) — 367 citations