Arkadiusz Kwasigroch

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 56 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 20 citations into it; #16,723 of 21,575 by trust here, #20,756 by citations
• Artificial Intelligence — 19 citations into it; #25,811 of 35,345 by trust here, #30,347 by citations
• Model Architectures — 11 citations into it
• Optimization & Training — 7 citations into it

Whom Arkadiusz Kwasigroch trusts overall

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

1. Karen Simonyan
2. Yann LeCun
3. Geoffrey E. Hinton
4. Kaiming He
5. Alex Krizhevsky
6. Andrew Zisserman
7. Yoshua Bengio
8. Ilya Sutskever
9. Sergey Ioffe
10. Ilya Loshchilov

Who trusts Arkadiusz Kwasigroch overall

1. Agnieszka Mikołajczyk
2. Michal Grochowski

Papers from Arkadiusz Kwasigroch's perspective

Ordered by how strongly the researchers Arkadiusz Kwasigroch 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Deep neural network architecture search using network morphism (2019) — 8 citations
• Deep neural networks approach to skin lesions classification — A comparative analysis (2017) — 56 citations